Codebook for EA Survey, 2020; uninformative variables removed

#eval=params$runcodebooks

eas_20 %>%    select_if(function(col) {!is.character(col) | n_distinct(as.numeric(col))<15}) %>%
 # detect_scales(quiet=TRUE) %>% 
codebook(., survey_repetition = "single", metadata_table = TRUE) #Gerhard: this could also create an html; or make this as a separate markdown. It takes a long time to run... so maybe don't do it here

Metadata

Description

Dataset name: .

The dataset has N=2164 rows and 310 columns. 0 rows have no missing values on any column.

Metadata for search engines

• Date published: 2021-03-03

x respondentid collectorid start_date end_date custom_data_1 opt_out_cea first_hear_ea_other first_hear_ea_desc involve_80k involve_givewell involve_personal_contact involve_book involve_article_blog involve_gwwc involve_group involve_online involve_lesswrong involve_slate_star involve_podcast involve_ea_global involve_lycs involve_ace involve_eagx involve_other action_chose_job_degree action_applied_job_degree action_donated action_gwwc action_organize_group action_work_ea_org action_change_major action_wrote_thesis action_internship action_applied_ea_global action_attended_ea_global action_ea_forum action_lead_group action_applied_one_on_one action_had_one_on_one action_change_career action_subscribe_80k action_none ea_org_or_project member_ea_fb member_ea_forum member_lesswrong member_ea_group member_none local_group_original group_comfortable_friend group_beliefs_humility group_supports_action influence_80k_one_on_one influence_80k_website influence_80k_podcast influence_podcast_other influence_personal_contact influence_books influence_gwwc influence_local_group influence_givewell influence_ea_global influence_eagx influence_ace influence_lycs influence_ea_forum influence_articles_blogs influence_ea_survey influence_facebook_groups influence_lesswrong influence_slate_star influence_wanbam influence_aac influence_none influence_other negative_80k negative_podcast negative_givewell negative_personal_contact negative_books negative_gwwc negative_local_group negative_lesswrong negative_slate_star negative_ea_global negative_eagx negative_facebook_group negative_ea_forum negative_articles_blogs negative_ea_fellowship negative_eagx2 negative_ea_newsletter negative_wanbam negative_none negative_other negative_response engaged_ea_forum engaged_online_community engaged_local_groups engaged_ea_fellowship engaged_gwwc engaged_ea_global engaged_eagx engaged_ea_newsletter engaged_wanbam engaged_personal_contact engaged_80k_podcast engaged_80k_hours engaged_80k_one_on_one engaged_givewell engaged_lesswrong engaged_slate_star substantial_affect_impact prioritize_animal_welfare prioritize_causes prioritize_climate_change prioritize_biosecurity prioritize_nuclear_security prioritize_ai_risks prioritize_mental_health prioritize_global_poverty prioritize_meta prioritize_ea_movement prioritize_x_risks prioritize_broad_longtermism prioritize_other currency currency_other income donation_2019 donation_2020 donate_later university_original birth_year gender_original sexual_orientation country city_other ea_community_ideal ea_community_satisfaction ea_community_why agree_ea_helps_impact agree_part_of_ea_community friend_introduce learned_80k connection_80k learned_ea_global connection_ea_global learned_ea_hub connection_ea_hub learned_ea_student_mentoring connection_ea_student_mentor learned_eagx connection_eagx learned_effective_thesis connection_effective_thesis learned_facebook_group connection_facebook_group learned_gwwc connection_gwwc learned_intl_ea_events connection_intl_ea_events learned_personal_connection connection_personal_contact learned_lesswrong connection_lesswrong learned_local_group connection_local_groups learned_non_local_group connection_non_local_group learned_ea_forum connection_ea_forum learned_ea_books connection_ea_books learned_ea_newsletter connection_ea_newsletter learned_none connection_none learned_connection_other participate_doing_good_better participate_the_precipice participate_fellowship_intro participate_fellowship_adv participate_80k_pod_discuss participate_fellowship_career participate_fellowship_causes participate_intro_one_on_one participate_gwwc_info_session participate_donation_discuss participate_social_event participate_contact email_next_survey email_followup_surveys email_dont_email share_80k dont_share_80k profile_ea_hub agree_quantify_compare_impact agree_ways_better_than_others agree_work_on_any_cause agree_farmed_animals_concern agree_longtermism reputation_effect_explanation bottleneck_productivity dislike_ea_community donate_rethink_charity donate_80k donate_center_applied_rational donate_mercy_for_animals donate_other1 donate_other2 donate_other3 donate_other4 donate_other5 datecreated group_name_original group_name_manual first_hear_qual _merge ea_id ea_id2 ea_id3 engagement capital_over_impact financial_instability first_generation_student reputation_effect year_involved first_hear_ea city collector_source gender_manual race_white race_black_aa race_hispanic_la_spanish race_american_indian_alaskan race_asian race_native_hawaiin_pacific race_prefer_no_answer race_other race_ status_employed_ft status_employed_pt status_self_employed status_not_employed_looking status_not_employed status_homemaker_parent status_retired status_student_hs status_student_undergrad status_student_masters status_student_doctoral status_student_other status_prefer_no_answer status_ career_still_deciding career_building_capital career_non_profit_ea career_non_profit career_for_profit_earn_to_give career_for_profit career_academia career_government career_think_tank_lobby career_na career_other career_ race age_approx employ_status age_approx_ranges age_approx_split engagement_num engagement_f d_engage_3_5 d_engage_4_5 d_engage_5 income_k d_male d_student d_live_usa prioritize_lt referrer referrer_cat referrer_min100 referrer_cat2 referrer_cat3 engage_cats_1 engage_cats_2 start_date_quantiles start_date_thirds_by_referrer survey_willing donation_2019_c donation_2020_c income_c income_k_c income_c_imp don_share_inc_19 don_share_inc_19_imp don_19_p1 income_c_imp_k action_gwwc_f top_priority_rating avg_priority_rating mn_priority_rating lt_top_priority lt_above_mn_priority top_priority_rating_among_lt mn_priority_lt_rating start_date_qtl_by_referrer

#Variables

respondentid

Respondent ID

Distribution

Distribution of values for respondentid

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
respondentid	Respondent ID	numeric	0	1	1.2e+10	1.2e+10	1.2e+10	1.2e+10	31898517	▆▆▇▃▂

collectorid

Collector ID

Distribution

Distribution of values for collectorid

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
collectorid	Collector ID	numeric	0	1	4e+08	4e+08	4e+08	4e+08	407595	▇▂▂▁▁

start_date

Start Date

Distribution

## 52  unique, categorical values, so not shown.

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	min	median	max
start_date	Start Date	Date	0	1	52	2020-11-13	2020-12-05	2021-01-03

end_date

End Date

Distribution

## 52  unique, categorical values, so not shown.

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	min	median	max
end_date	End Date	Date	0	1	52	2020-11-13	2020-12-05	2021-01-03

custom_data_1

Custom Data 1

Distribution

## No non-missing values to show.

2164 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	hist
custom_data_1	Custom Data 1	numeric	2164	0	NA	NA	NA

opt_out_cea

Opt out of data sharing with the Centre for Effective Altruism

Distribution

Distribution of values for opt_out_cea

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
opt_out_cea	Opt out of data sharing with the Centre for Effective Altruism	character	0	1	2	2046	0	78	0

first_hear_ea_other

How did you first hear about effective altruism? Other

Distribution

Distribution of values for first_hear_ea_other

1997 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
first_hear_ea_other	How did you first hear about effective altruism? Other	character	1997	0.08	145	0	3	339	0

first_hear_ea_desc

Please briefly specify any further details about how you first heard about EA.

Distribution

Distribution of values for first_hear_ea_desc

968 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
first_hear_ea_desc	Please briefly specify any further details about how you first heard about EA.	character	968	0.55	1144	0	1	609	0

involve_80k

Important for you getting involved in EA? 80,000 Hours

Distribution

Distribution of values for involve_80k

290 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
involve_80k	Important for you getting involved in EA? 80,000 Hours	numeric	290	0.87	0	1	1	0.51	0.5	▇▁▁▁▇

involve_givewell

Important for you getting involved in EA? GiveWell

Distribution

Distribution of values for involve_givewell

290 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
involve_givewell	Important for you getting involved in EA? GiveWell	numeric	290	0.87	0	0	1	0.35	0.48	▇▁▁▁▅

involve_personal_contact

Important for you getting involved in EA? Personal contact with EAs

Distribution

Distribution of values for involve_personal_contact

290 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
involve_personal_contact	Important for you getting involved in EA? Personal contact with EAs	numeric	290	0.87	0	0	1	0.35	0.48	▇▁▁▁▅

involve_book

Important for you getting involved in EA? A book

Distribution

Distribution of values for involve_book

290 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
involve_book	Important for you getting involved in EA? A book	numeric	290	0.87	0	0	1	0.23	0.42	▇▁▁▁▂

involve_article_blog

Important for you getting involved in EA? An article or blog

Distribution

Distribution of values for involve_article_blog

290 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
involve_article_blog	Important for you getting involved in EA? An article or blog	numeric	290	0.87	0	0	1	0.17	0.37	▇▁▁▁▂

involve_gwwc

Important for you getting involved in EA? Giving What We Can

Distribution

Distribution of values for involve_gwwc

290 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
involve_gwwc	Important for you getting involved in EA? Giving What We Can	numeric	290	0.87	0	0	1	0.21	0.41	▇▁▁▁▂

involve_group

Important for you getting involved in EA? Local or university EA Group

Distribution

Distribution of values for involve_group

290 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
involve_group	Important for you getting involved in EA? Local or university EA Group	numeric	290	0.87	0	0	1	0.29	0.45	▇▁▁▁▃

involve_online

Important for you getting involved in EA? The online EA community

Distribution

Distribution of values for involve_online

290 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
involve_online	Important for you getting involved in EA? The online EA community	numeric	290	0.87	0	0	1	0.2	0.4	▇▁▁▁▂

involve_lesswrong

Important for you getting involved in EA? LessWrong

Distribution

Distribution of values for involve_lesswrong

290 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
involve_lesswrong	Important for you getting involved in EA? LessWrong	numeric	290	0.87	0	0	1	0.18	0.39	▇▁▁▁▂

involve_slate_star

Important for you getting involved in EA? Slate Star Codex

Distribution

Distribution of values for involve_slate_star

290 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
involve_slate_star	Important for you getting involved in EA? Slate Star Codex	numeric	290	0.87	0	0	1	0.17	0.38	▇▁▁▁▂

involve_podcast

Important for you getting involved in EA? Podcast

Distribution

Distribution of values for involve_podcast

290 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
involve_podcast	Important for you getting involved in EA? Podcast	numeric	290	0.87	0	0	1	0.2	0.4	▇▁▁▁▂

involve_ea_global

Important for you getting involved in EA? EA Global

Distribution

Distribution of values for involve_ea_global

290 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
involve_ea_global	Important for you getting involved in EA? EA Global	numeric	290	0.87	0	0	1	0.1	0.3	▇▁▁▁▁

involve_lycs

Important for you getting involved in EA? The Life You Can Save

Distribution

Distribution of values for involve_lycs

290 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
involve_lycs	Important for you getting involved in EA? The Life You Can Save	numeric	290	0.87	0	0	1	0.12	0.33	▇▁▁▁▁

involve_ace

Important for you getting involved in EA? Animal Charity Evaluators

Distribution

Distribution of values for involve_ace

290 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
involve_ace	Important for you getting involved in EA? Animal Charity Evaluators	numeric	290	0.87	0	0	1	0.06	0.23	▇▁▁▁▁

involve_eagx

Important for you getting involved in EA? EAGx

Distribution

Distribution of values for involve_eagx

290 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
involve_eagx	Important for you getting involved in EA? EAGx	numeric	290	0.87	0	0	1	0.07	0.26	▇▁▁▁▁

involve_other

Important for you getting involved in EA? Other (please specify)

Distribution

Distribution of values for involve_other

290 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
involve_other	Important for you getting involved in EA? Other (please specify)	numeric	290	0.87	0	0	1	0.1	0.3	▇▁▁▁▁

action_chose_job_degree

Action: Chose a job or graduate degree program based on EA principles

Distribution

Distribution of values for action_chose_job_degree

280 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
action_chose_job_degree	Action: Chose a job or graduate degree program based on EA principles	numeric	280	0.87	0	0	1	0.28	0.45	▇▁▁▁▃

action_applied_job_degree

Action: Applied for a job or graduate degree program based on EA principles

Distribution

Distribution of values for action_applied_job_degree

280 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
action_applied_job_degree	Action: Applied for a job or graduate degree program based on EA principles	numeric	280	0.87	0	0	1	0.28	0.45	▇▁▁▁▃

action_donated

Action: Donated >10% of your income based on EA principles

Distribution

Distribution of values for action_donated

280 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
action_donated	Action: Donated >10% of your income based on EA principles	numeric	280	0.87	0	0	1	0.32	0.47	▇▁▁▁▃

action_gwwc

Action: Took the Giving What We Can pledge

Distribution

Distribution of values for action_gwwc

280 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
action_gwwc	Action: Took the Giving What We Can pledge	numeric	280	0.87	0	0	1	0.3	0.46	▇▁▁▁▃

action_organize_group

Action: Spent >6 hours/week for >=2 months organizing an EA group/project

Distribution

Distribution of values for action_organize_group

280 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
action_organize_group	Action: Spent >6 hours/week for >=2 months organizing an EA group/project	numeric	280	0.87	0	0	1	0.24	0.42	▇▁▁▁▂

action_work_ea_org

Action: Worked (or currently work) at an EA organization

Distribution

Distribution of values for action_work_ea_org

280 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
action_work_ea_org	Action: Worked (or currently work) at an EA organization	numeric	280	0.87	0	0	1	0.16	0.37	▇▁▁▁▂

action_change_major

Action: Changed your major in university based on EA principles

Distribution

Distribution of values for action_change_major

280 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
action_change_major	Action: Changed your major in university based on EA principles	numeric	280	0.87	0	0	1	0.09	0.29	▇▁▁▁▁

action_wrote_thesis

Action: Wrote a thesis based on EA principles

Distribution

Distribution of values for action_wrote_thesis

280 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
action_wrote_thesis	Action: Wrote a thesis based on EA principles	numeric	280	0.87	0	0	1	0.05	0.22	▇▁▁▁▁

action_internship

Action: Internship related to a career path you are exploring based on EA

Distribution

Distribution of values for action_internship

280 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
action_internship	Action: Internship related to a career path you are exploring based on EA	numeric	280	0.87	0	0	1	0.12	0.33	▇▁▁▁▁

action_applied_ea_global

Action: Applied to EA Global

Distribution

Distribution of values for action_applied_ea_global

280 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
action_applied_ea_global	Action: Applied to EA Global	numeric	280	0.87	0	0	1	0.28	0.45	▇▁▁▁▃

action_attended_ea_global

Action: Attended EA Global

Distribution

Distribution of values for action_attended_ea_global

280 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
action_attended_ea_global	Action: Attended EA Global	numeric	280	0.87	0	0	1	0.29	0.45	▇▁▁▁▃

action_ea_forum

Action: Posted or commented on the EA Forum

Distribution

Distribution of values for action_ea_forum

280 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
action_ea_forum	Action: Posted or commented on the EA Forum	numeric	280	0.87	0	0	1	0.26	0.44	▇▁▁▁▃

action_lead_group

Action: Been a leader of a local EA group

Distribution

Distribution of values for action_lead_group

280 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
action_lead_group	Action: Been a leader of a local EA group	numeric	280	0.87	0	0	1	0.21	0.41	▇▁▁▁▂

action_applied_one_on_one

Action: Applied for a one-on-one career discussion with 80,000 Hours

Distribution

Distribution of values for action_applied_one_on_one

280 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
action_applied_one_on_one	Action: Applied for a one-on-one career discussion with 80,000 Hours	numeric	280	0.87	0	0	1	0.21	0.41	▇▁▁▁▂

action_had_one_on_one

Action: Had a one-on-one career discussion with 80,000 Hours

Distribution

Distribution of values for action_had_one_on_one

280 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
action_had_one_on_one	Action: Had a one-on-one career discussion with 80,000 Hours	numeric	280	0.87	0	0	1	0.13	0.33	▇▁▁▁▁

action_change_career

Action: Changed your career plans based on EA principles

Distribution

Distribution of values for action_change_career

280 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
action_change_career	Action: Changed your career plans based on EA principles	numeric	280	0.87	0	0	1	0.44	0.5	▇▁▁▁▆

action_subscribe_80k

Action: Subscribed to the 80,000 Hours newsletter

Distribution

Distribution of values for action_subscribe_80k

280 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
action_subscribe_80k	Action: Subscribed to the 80,000 Hours newsletter	numeric	280	0.87	0	1	1	0.53	0.5	▇▁▁▁▇

action_none

Action: None of the above

Distribution

Distribution of values for action_none

280 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
action_none	Action: None of the above	numeric	280	0.87	0	0	1	0.13	0.33	▇▁▁▁▁

ea_org_or_project

Name of EA org/project you worked on or interned for.

Distribution

Distribution of values for ea_org_or_project

1719 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
ea_org_or_project	Name of EA org/project you worked on or interned for.	character	1719	0.21	387	0	3	403	0

member_ea_fb

Which of the following are you a member of? EA Facebook group

Distribution

Distribution of values for member_ea_fb

310 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
member_ea_fb	Which of the following are you a member of? EA Facebook group	numeric	310	0.86	0	0	1	0.48	0.5	▇▁▁▁▇

member_ea_forum

Which of the following are you a member of? The Effective Altruism Forum

Distribution

Distribution of values for member_ea_forum

310 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
member_ea_forum	Which of the following are you a member of? The Effective Altruism Forum	numeric	310	0.86	0	0	1	0.38	0.49	▇▁▁▁▅

member_lesswrong

Which of the following are you a member of? LessWrong

Distribution

Distribution of values for member_lesswrong

310 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
member_lesswrong	Which of the following are you a member of? LessWrong	numeric	310	0.86	0	0	1	0.23	0.42	▇▁▁▁▂

member_ea_group

Which of the following are you a member of? Local EA group

Distribution

Distribution of values for member_ea_group

310 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
member_ea_group	Which of the following are you a member of? Local EA group	numeric	310	0.86	0	0	1	0.5	0.5	▇▁▁▁▇

member_none

Which of the following are you a member of? None of the above

Distribution

Distribution of values for member_none

310 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
member_none	Which of the following are you a member of? None of the above	numeric	310	0.86	0	0	1	0.25	0.44	▇▁▁▁▃

local_group_original

If you are a member of a local EA group, which group are you a member of?

Distribution

Distribution of values for local_group_original

1294 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
local_group_original	If you are a member of a local EA group, which group are you a member of?	character	1294	0.4	442	0	5	324	0

group_comfortable_friend

My group is a place to which I’d feel comfortable bringing a friend

Distribution

Distribution of values for group_comfortable_friend

1290 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
group_comfortable_friend	My group is a place to which I’d feel comfortable bringing a friend	factor	FALSE	Strongly disagree, 2. (2) Disagree, 3. (3) Neither agree nor disagree, 4. (4) Agree, 5. (5) Strongly agree	1290	0.4	5	(5): 448, (4): 310, (3): 87, (2): 22

group_beliefs_humility

My group is a place where people express their beliefs with humility

Distribution

Distribution of values for group_beliefs_humility

1300 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
group_beliefs_humility	My group is a place where people express their beliefs with humility	factor	FALSE	Strongly disagree, 2. (2) Disagree, 3. (3) Neither agree nor disagree, 4. (4) Agree, 5. (5) Strongly agree	1300	0.4	5	(4): 388, (5): 302, (3): 143, (2): 25

group_supports_action

My group supports me in taking action based on EA principles

Distribution

Distribution of values for group_supports_action

1297 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
group_supports_action	My group supports me in taking action based on EA principles	factor	FALSE	Strongly disagree, 2. (2) Disagree, 3. (3) Neither agree nor disagree, 4. (4) Agree, 5. (5) Strongly agree	1297	0.4	5	(5): 404, (4): 336, (3): 111, (2): 12

influence_80k_one_on_one

Influence your ability to make impact? 80,000 Hours (1-on-1 career discussion)

Distribution

Distribution of values for influence_80k_one_on_one

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_80k_one_on_one	Influence your ability to make impact? 80,000 Hours (1-on-1 career discussion)	numeric	413	0.81	0	0	1	0.04	0.19	▇▁▁▁▁

influence_80k_website

Influence your ability to make impact? 80,000 Hours (website)

Distribution

Distribution of values for influence_80k_website

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_80k_website	Influence your ability to make impact? 80,000 Hours (website)	numeric	413	0.81	0	0	1	0.37	0.48	▇▁▁▁▅

influence_80k_podcast

Influence your ability to make impact? 80,000 Hours (podcast)

Distribution

Distribution of values for influence_80k_podcast

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_80k_podcast	Influence your ability to make impact? 80,000 Hours (podcast)	numeric	413	0.81	0	0	1	0.21	0.4	▇▁▁▁▂

influence_podcast_other

Influence your ability to make impact? Podcast (other than 80,000 Hours)

Distribution

Distribution of values for influence_podcast_other

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_podcast_other	Influence your ability to make impact? Podcast (other than 80,000 Hours)	numeric	413	0.81	0	0	1	0.09	0.28	▇▁▁▁▁

influence_personal_contact

Influence your ability to make impact? Personal contact with EAs

Distribution

Distribution of values for influence_personal_contact

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_personal_contact	Influence your ability to make impact? Personal contact with EAs	numeric	413	0.81	0	0	1	0.39	0.49	▇▁▁▁▅

influence_books

Influence your ability to make impact? Books related to EA

Distribution

Distribution of values for influence_books

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_books	Influence your ability to make impact? Books related to EA	numeric	413	0.81	0	0	1	0.21	0.41	▇▁▁▁▂

influence_gwwc

Influence your ability to make impact? Giving What We Can

Distribution

Distribution of values for influence_gwwc

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_gwwc	Influence your ability to make impact? Giving What We Can	numeric	413	0.81	0	0	1	0.14	0.35	▇▁▁▁▁

influence_local_group

Influence your ability to make impact? Local EA groups

Distribution

Distribution of values for influence_local_group

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_local_group	Influence your ability to make impact? Local EA groups	numeric	413	0.81	0	0	1	0.26	0.44	▇▁▁▁▃

influence_givewell

Influence your ability to make impact? GiveWell

Distribution

Distribution of values for influence_givewell

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_givewell	Influence your ability to make impact? GiveWell	numeric	413	0.81	0	0	1	0.32	0.47	▇▁▁▁▃

influence_ea_global

Influence your ability to make impact? EA Global

Distribution

Distribution of values for influence_ea_global

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_ea_global	Influence your ability to make impact? EA Global	numeric	413	0.81	0	0	1	0.1	0.3	▇▁▁▁▁

influence_eagx

Influence your ability to make impact? EAGx

Distribution

Distribution of values for influence_eagx

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_eagx	Influence your ability to make impact? EAGx	numeric	413	0.81	0	0	1	0.06	0.24	▇▁▁▁▁

influence_ace

Influence your ability to make impact? Animal Charity Evaluators

Distribution

Distribution of values for influence_ace

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_ace	Influence your ability to make impact? Animal Charity Evaluators	numeric	413	0.81	0	0	1	0.06	0.24	▇▁▁▁▁

influence_lycs

Influence your ability to make impact? The Life You Can Save

Distribution

Distribution of values for influence_lycs

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_lycs	Influence your ability to make impact? The Life You Can Save	numeric	413	0.81	0	0	1	0.09	0.28	▇▁▁▁▁

influence_ea_forum

Influence your ability to make impact? The EA Forum

Distribution

Distribution of values for influence_ea_forum

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_ea_forum	Influence your ability to make impact? The EA Forum	numeric	413	0.81	0	0	1	0.12	0.33	▇▁▁▁▁

influence_articles_blogs

Influence your ability to make impact? Articles/blogs related to EA

Distribution

Distribution of values for influence_articles_blogs

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_articles_blogs	Influence your ability to make impact? Articles/blogs related to EA	numeric	413	0.81	0	0	1	0.15	0.36	▇▁▁▁▂

influence_ea_survey

Influence your ability to make impact? The EA Newsletter

Distribution

Distribution of values for influence_ea_survey

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_ea_survey	Influence your ability to make impact? The EA Newsletter	numeric	413	0.81	0	0	1	0.06	0.23	▇▁▁▁▁

influence_facebook_groups

Influence your ability to make impact? Facebook groups related to EA

Distribution

Distribution of values for influence_facebook_groups

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_facebook_groups	Influence your ability to make impact? Facebook groups related to EA	numeric	413	0.81	0	0	1	0.07	0.26	▇▁▁▁▁

influence_lesswrong

Influence your ability to make impact? LessWrong

Distribution

Distribution of values for influence_lesswrong

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_lesswrong	Influence your ability to make impact? LessWrong	numeric	413	0.81	0	0	1	0.12	0.32	▇▁▁▁▁

influence_slate_star

Influence your ability to make impact? Slate Star Codex

Distribution

Distribution of values for influence_slate_star

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_slate_star	Influence your ability to make impact? Slate Star Codex	numeric	413	0.81	0	0	1	0.12	0.32	▇▁▁▁▁

influence_wanbam

Influence your ability to make impact? WANBAM

Distribution

Distribution of values for influence_wanbam

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_wanbam	Influence your ability to make impact? WANBAM	numeric	413	0.81	0	0	1	0.01	0.1	▇▁▁▁▁

influence_aac

Influence your ability to make impact? Animal Advocacy Careers

Distribution

Distribution of values for influence_aac

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_aac	Influence your ability to make impact? Animal Advocacy Careers	numeric	413	0.81	0	0	1	0.01	0.11	▇▁▁▁▁

influence_none

Influence your ability to make impact? None of the above

Distribution

Distribution of values for influence_none

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_none	Influence your ability to make impact? None of the above	numeric	413	0.81	0	0	1	0.03	0.18	▇▁▁▁▁

influence_other

Influence your ability to make impact? Other

Distribution

Distribution of values for influence_other

413 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
influence_other	Influence your ability to make impact? Other	numeric	413	0.81	0	0	1	0.09	0.29	▇▁▁▁▁

negative_80k

Negative impact on your involvement with EA so far? 80,000 Hours

Distribution

Distribution of values for negative_80k

1026 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
negative_80k	Negative impact on your involvement with EA so far? 80,000 Hours	numeric	1026	0.53	0	0	1	0.1	0.29	▇▁▁▁▁

negative_podcast

Negative impact on your involvement with EA so far? Podcast (not 80,000 Hours)

Distribution

Distribution of values for negative_podcast

1026 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
negative_podcast	Negative impact on your involvement with EA so far? Podcast (not 80,000 Hours)	numeric	1026	0.53	0	0	1	0.01	0.07	▇▁▁▁▁

negative_givewell

Negative impact on your involvement with EA so far? GiveWell

Distribution

Distribution of values for negative_givewell

1026 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
negative_givewell	Negative impact on your involvement with EA so far? GiveWell	numeric	1026	0.53	0	0	1	0.01	0.08	▇▁▁▁▁

negative_personal_contact

Negative impact on your involvement with EA so far? Personal contact with EAs

Distribution

Distribution of values for negative_personal_contact

1026 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
negative_personal_contact	Negative impact on your involvement with EA so far? Personal contact with EAs	numeric	1026	0.53	0	0	1	0.13	0.34	▇▁▁▁▁

negative_books

Negative impact on your involvement with EA so far? Books related to EA

Distribution

Distribution of values for negative_books

1026 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
negative_books	Negative impact on your involvement with EA so far? Books related to EA	numeric	1026	0.53	0	0	1	0.01	0.1	▇▁▁▁▁

negative_gwwc

Negative impact on your involvement with EA so far? Giving What We Can

Distribution

Distribution of values for negative_gwwc

1026 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
negative_gwwc	Negative impact on your involvement with EA so far? Giving What We Can	numeric	1026	0.53	0	0	1	0.01	0.11	▇▁▁▁▁

negative_local_group

Negative impact on your involvement with EA so far? Local EA groups

Distribution

Distribution of values for negative_local_group

1026 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
negative_local_group	Negative impact on your involvement with EA so far? Local EA groups	numeric	1026	0.53	0	0	1	0.07	0.25	▇▁▁▁▁

negative_lesswrong

Negative impact on your involvement with EA so far? LessWrong

Distribution

Distribution of values for negative_lesswrong

1026 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
negative_lesswrong	Negative impact on your involvement with EA so far? LessWrong	numeric	1026	0.53	0	0	1	0.08	0.27	▇▁▁▁▁

negative_slate_star

Negative impact on your involvement with EA so far? SlateStarCodex

Distribution

Distribution of values for negative_slate_star

1026 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
negative_slate_star	Negative impact on your involvement with EA so far? SlateStarCodex	numeric	1026	0.53	0	0	1	0.03	0.18	▇▁▁▁▁

negative_ea_global

Negative impact on your involvement with EA so far? EA Global

Distribution

Distribution of values for negative_ea_global

1026 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
negative_ea_global	Negative impact on your involvement with EA so far? EA Global	numeric	1026	0.53	0	0	1	0.04	0.18	▇▁▁▁▁

negative_eagx

Negative impact on your involvement with EA so far? EAGx

Distribution

Distribution of values for negative_eagx

1026 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
negative_eagx	Negative impact on your involvement with EA so far? EAGx	numeric	1026	0.53	0	0	1	0.01	0.09	▇▁▁▁▁

negative_facebook_group

Negative impact on your involvement with EA so far? FB groups related to EA

Distribution

Distribution of values for negative_facebook_group

1026 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
negative_facebook_group	Negative impact on your involvement with EA so far? FB groups related to EA	numeric	1026	0.53	0	0	1	0.06	0.24	▇▁▁▁▁

negative_ea_forum

Negative impact on your involvement with EA so far? The EA Forum

Distribution

Distribution of values for negative_ea_forum

1026 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
negative_ea_forum	Negative impact on your involvement with EA so far? The EA Forum	numeric	1026	0.53	0	0	1	0.07	0.25	▇▁▁▁▁

negative_articles_blogs

Negative impact on your involvement with EA so far? Articles/blogs related EA

Distribution

Distribution of values for negative_articles_blogs

1026 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
negative_articles_blogs	Negative impact on your involvement with EA so far? Articles/blogs related EA	numeric	1026	0.53	0	0	1	0.04	0.18	▇▁▁▁▁

negative_ea_fellowship

Negative impact on your involvement with EA so far? An EA Fellowship

Distribution

Distribution of values for negative_ea_fellowship

1026 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
negative_ea_fellowship	Negative impact on your involvement with EA so far? An EA Fellowship	numeric	1026	0.53	0	0	1	0	0.06	▇▁▁▁▁

negative_eagx2

Negative impact on your involvement with EA so far? EAGx

Distribution

Distribution of values for negative_eagx2

1026 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
negative_eagx2	Negative impact on your involvement with EA so far? EAGx	numeric	1026	0.53	0	0	1	0.01	0.07	▇▁▁▁▁

negative_ea_newsletter

Negative impact on your involvement with EA so far? The EA Newsletter

Distribution

Distribution of values for negative_ea_newsletter

1026 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
negative_ea_newsletter	Negative impact on your involvement with EA so far? The EA Newsletter	numeric	1026	0.53	0	0	1	0	0.04	▇▁▁▁▁

negative_wanbam

Negative impact on your involvement with EA so far? WANBAM

Distribution

Distribution of values for negative_wanbam

1026 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
negative_wanbam	Negative impact on your involvement with EA so far? WANBAM	numeric	1026	0.53	0	0	1	0.01	0.09	▇▁▁▁▁

negative_none

Negative impact on your involvement with EA so far? None of the above

Distribution

Distribution of values for negative_none

1026 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
negative_none	Negative impact on your involvement with EA so far? None of the above	numeric	1026	0.53	0	1	1	0.57	0.49	▆▁▁▁▇

negative_other

Negative impact on your involvement with EA so far? Other

Distribution

Distribution of values for negative_other

1026 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
negative_other	Negative impact on your involvement with EA so far? Other	numeric	1026	0.53	0	0	1	0.09	0.28	▇▁▁▁▁

negative_response

Negative impact on your involvement with EA so far? Open-Ended Response

Distribution

Distribution of values for negative_response

1809 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
negative_response	Negative impact on your involvement with EA so far? Open-Ended Response	character	1809	0.16	349	0	2	1753	0

engaged_ea_forum

Affected your likelihood of staying engaged with EA? The EA Forum

Distribution

Distribution of values for engaged_ea_forum

1443 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
engaged_ea_forum	Affected your likelihood of staying engaged with EA? The EA Forum	factor	FALSE	Made me a lot less likely to stay engaged, 2. Made me less likely to stay engaged, 3. Made me slightly less likely to stay engaged, 4. Significant interaction, but neutral effect, 5. Made me slightly more likely to stay engaged, 6. Made me more likely to stay engaged, 7. Made me a lot more likely to stay engaged	1443	0.33	7	Mad: 310, Mad: 184, Sig: 122, Mad: 44

engaged_online_community

Affected your likelihood of staying engaged with EA? The online EA community

Distribution

Distribution of values for engaged_online_community

1362 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
engaged_online_community	Affected your likelihood of staying engaged with EA? The online EA community	factor	FALSE	Made me a lot less likely to stay engaged, 2. Made me less likely to stay engaged, 3. Made me slightly less likely to stay engaged, 4. Significant interaction, but neutral effect, 5. Made me slightly more likely to stay engaged, 6. Made me more likely to stay engaged, 7. Made me a lot more likely to stay engaged	1362	0.37	7	Mad: 342, Mad: 181, Sig: 120, Mad: 88

engaged_local_groups

Affected your likelihood of staying engaged with EA? Local EA groups

Distribution

Distribution of values for engaged_local_groups

1320 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
engaged_local_groups	Affected your likelihood of staying engaged with EA? Local EA groups	factor	FALSE	Made me a lot less likely to stay engaged, 2. Made me less likely to stay engaged, 3. Made me slightly less likely to stay engaged, 4. Significant interaction, but neutral effect, 5. Made me slightly more likely to stay engaged, 6. Made me more likely to stay engaged, 7. Made me a lot more likely to stay engaged	1320	0.39	7	Mad: 269, Mad: 265, Mad: 193, Sig: 68

engaged_ea_fellowship

Affected your likelihood of staying engaged with EA? An EA Fellowship

Distribution

Distribution of values for engaged_ea_fellowship

1937 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
engaged_ea_fellowship	Affected your likelihood of staying engaged with EA? An EA Fellowship	factor	FALSE	Made me a lot less likely to stay engaged, 2. Made me less likely to stay engaged, 3. Made me slightly less likely to stay engaged, 4. Significant interaction, but neutral effect, 5. Made me slightly more likely to stay engaged, 6. Made me more likely to stay engaged, 7. Made me a lot more likely to stay engaged	1937	0.1	6	Mad: 81, Mad: 74, Mad: 43, Sig: 23

engaged_gwwc

Affected your likelihood of staying engaged with EA? Giving What We Can

Distribution

Distribution of values for engaged_gwwc

1673 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
engaged_gwwc	Affected your likelihood of staying engaged with EA? Giving What We Can	factor	FALSE	Made me a lot less likely to stay engaged, 2. Made me less likely to stay engaged, 3. Made me slightly less likely to stay engaged, 4. Significant interaction, but neutral effect, 5. Made me slightly more likely to stay engaged, 6. Made me more likely to stay engaged, 7. Made me a lot more likely to stay engaged	1673	0.23	7	Mad: 207, Mad: 128, Sig: 75, Mad: 64

engaged_ea_global

Affected your likelihood of staying engaged with EA? EA Global

Distribution

Distribution of values for engaged_ea_global

1790 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
engaged_ea_global	Affected your likelihood of staying engaged with EA? EA Global	factor	FALSE	Made me a lot less likely to stay engaged, 2. Made me less likely to stay engaged, 3. Made me slightly less likely to stay engaged, 4. Significant interaction, but neutral effect, 5. Made me slightly more likely to stay engaged, 6. Made me more likely to stay engaged, 7. Made me a lot more likely to stay engaged	1790	0.17	7	Mad: 138, Mad: 87, Sig: 66, Mad: 63

engaged_eagx

Affected your likelihood of staying engaged with EA? EAGx

Distribution

Distribution of values for engaged_eagx

1775 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
engaged_eagx	Affected your likelihood of staying engaged with EA? EAGx	factor	FALSE	Made me a lot less likely to stay engaged, 2. Made me less likely to stay engaged, 3. Made me slightly less likely to stay engaged, 4. Significant interaction, but neutral effect, 5. Made me slightly more likely to stay engaged, 6. Made me more likely to stay engaged, 7. Made me a lot more likely to stay engaged	1775	0.18	7	Mad: 139, Mad: 104, Sig: 67, Mad: 65

engaged_ea_newsletter

Affected your likelihood of staying engaged with EA? The EA Newsletter

Distribution

Distribution of values for engaged_ea_newsletter

1528 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
engaged_ea_newsletter	Affected your likelihood of staying engaged with EA? The EA Newsletter	factor	FALSE	Made me a lot less likely to stay engaged, 2. Made me less likely to stay engaged, 3. Made me slightly less likely to stay engaged, 4. Significant interaction, but neutral effect, 5. Made me slightly more likely to stay engaged, 6. Made me more likely to stay engaged, 7. Made me a lot more likely to stay engaged	1528	0.29	7	Mad: 310, Sig: 172, Mad: 113, Mad: 22

engaged_wanbam

Affected your likelihood of staying engaged with EA? WANBAM

Distribution

Distribution of values for engaged_wanbam

2055 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
engaged_wanbam	Affected your likelihood of staying engaged with EA? WANBAM	factor	FALSE	Made me a lot less likely to stay engaged, 2. Made me less likely to stay engaged, 3. Made me slightly less likely to stay engaged, 4. Significant interaction, but neutral effect, 5. Made me slightly more likely to stay engaged, 6. Made me more likely to stay engaged, 7. Made me a lot more likely to stay engaged	2055	0.05	7	Mad: 29, Sig: 26, Mad: 21, Mad: 19

engaged_personal_contact

Affected your likelihood of staying engaged with EA? Personal contacts

Distribution

Distribution of values for engaged_personal_contact

1068 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
engaged_personal_contact	Affected your likelihood of staying engaged with EA? Personal contacts	factor	FALSE	Made me a lot less likely to stay engaged, 2. Made me less likely to stay engaged, 3. Made me slightly less likely to stay engaged, 4. Significant interaction, but neutral effect, 5. Made me slightly more likely to stay engaged, 6. Made me more likely to stay engaged, 7. Made me a lot more likely to stay engaged	1068	0.51	7	Mad: 380, Mad: 356, Mad: 251, Sig: 74

engaged_80k_podcast

Affected your likelihood of staying engaged with EA? 80,000 Hours (podcast)

Distribution

Distribution of values for engaged_80k_podcast

1298 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
engaged_80k_podcast	Affected your likelihood of staying engaged with EA? 80,000 Hours (podcast)	factor	FALSE	Made me a lot less likely to stay engaged, 2. Made me less likely to stay engaged, 3. Made me slightly less likely to stay engaged, 4. Significant interaction, but neutral effect, 5. Made me slightly more likely to stay engaged, 6. Made me more likely to stay engaged, 7. Made me a lot more likely to stay engaged	1298	0.4	7	Mad: 371, Mad: 223, Sig: 139, Mad: 97

engaged_80k_hours

Affected your likelihood of staying engaged with EA? 80,000 Hours (website)

Distribution

Distribution of values for engaged_80k_hours

1234 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
engaged_80k_hours	Affected your likelihood of staying engaged with EA? 80,000 Hours (website)	factor	FALSE	Made me a lot less likely to stay engaged, 2. Made me less likely to stay engaged, 3. Made me slightly less likely to stay engaged, 4. Significant interaction, but neutral effect, 5. Made me slightly more likely to stay engaged, 6. Made me more likely to stay engaged, 7. Made me a lot more likely to stay engaged	1234	0.43	7	Mad: 396, Mad: 230, Sig: 139, Mad: 111

engaged_80k_one_on_one

Affected your likelihood of staying engaged with EA? 80k Hours (1-on-1 career)

Distribution

Distribution of values for engaged_80k_one_on_one

2045 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
engaged_80k_one_on_one	Affected your likelihood of staying engaged with EA? 80k Hours (1-on-1 career)	factor	FALSE	Made me a lot less likely to stay engaged, 2. Made me less likely to stay engaged, 3. Made me slightly less likely to stay engaged, 4. Significant interaction, but neutral effect, 5. Made me slightly more likely to stay engaged, 6. Made me more likely to stay engaged, 7. Made me a lot more likely to stay engaged	2045	0.05	7	Mad: 35, Mad: 25, Sig: 24, Mad: 20

engaged_givewell

Affected your likelihood of staying engaged with EA? GiveWell

Distribution

Distribution of values for engaged_givewell

1410 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
engaged_givewell	Affected your likelihood of staying engaged with EA? GiveWell	factor	FALSE	Made me a lot less likely to stay engaged, 2. Made me less likely to stay engaged, 3. Made me slightly less likely to stay engaged, 4. Significant interaction, but neutral effect, 5. Made me slightly more likely to stay engaged, 6. Made me more likely to stay engaged, 7. Made me a lot more likely to stay engaged	1410	0.35	7	Mad: 311, Mad: 244, Sig: 89, Mad: 87

engaged_lesswrong

Affected your likelihood of staying engaged with EA? LessWrong

Distribution

Distribution of values for engaged_lesswrong

1601 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
engaged_lesswrong	Affected your likelihood of staying engaged with EA? LessWrong	factor	FALSE	Made me a lot less likely to stay engaged, 2. Made me less likely to stay engaged, 3. Made me slightly less likely to stay engaged, 4. Significant interaction, but neutral effect, 5. Made me slightly more likely to stay engaged, 6. Made me more likely to stay engaged, 7. Made me a lot more likely to stay engaged	1601	0.26	7	Mad: 205, Sig: 153, Mad: 94, Mad: 50

engaged_slate_star

Affected your likelihood of staying engaged with EA? Slate Star Codex

Distribution

Distribution of values for engaged_slate_star

1589 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
engaged_slate_star	Affected your likelihood of staying engaged with EA? Slate Star Codex	factor	FALSE	Made me a lot less likely to stay engaged, 2. Made me less likely to stay engaged, 3. Made me slightly less likely to stay engaged, 4. Significant interaction, but neutral effect, 5. Made me slightly more likely to stay engaged, 6. Made me more likely to stay engaged, 7. Made me a lot more likely to stay engaged	1589	0.27	7	Mad: 198, Sig: 186, Mad: 112, Mad: 30

substantial_affect_impact

Are there other things which have substantially affected your impact?

Distribution

Distribution of values for substantial_affect_impact

1699 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
substantial_affect_impact	Are there other things which have substantially affected your impact?	character	1699	0.21	454	0	2	2642	0

prioritize_animal_welfare

Distribution

Distribution of values for prioritize_animal_welfare

561 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
prioritize_animal_welfare	factor	FALSE	1, 2. 2, 3. 3, 4. 4, 5. 5	561	0.74	5	3: 576, 4: 455, 2: 316, 5: 158	NA

prioritize_causes

Distribution

Distribution of values for prioritize_causes

689 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
prioritize_causes	factor	FALSE	1, 2. 2, 3. 3, 4. 4, 5. 5	689	0.68	5	4: 509, 3: 434, 5: 278, 2: 228	NA

prioritize_climate_change

Distribution

Distribution of values for prioritize_climate_change

561 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
prioritize_climate_change	factor	FALSE	1, 2. 2, 3. 3, 4. 4, 5. 5	561	0.74	5	3: 433, 4: 432, 2: 339, 5: 307	NA

prioritize_biosecurity

Distribution

Distribution of values for prioritize_biosecurity

583 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
prioritize_biosecurity	factor	FALSE	1, 2. 2, 3. 3, 4. 4, 5. 5	583	0.73	5	4: 657, 3: 532, 2: 224, 5: 136	NA

prioritize_nuclear_security

Distribution

Distribution of values for prioritize_nuclear_security

652 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
prioritize_nuclear_security	factor	FALSE	1, 2. 2, 3. 3, 4. 4, 5. 5	652	0.7	5	3: 593, 2: 385, 4: 369, 5: 92	NA

prioritize_ai_risks

Distribution

Distribution of values for prioritize_ai_risks

601 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
prioritize_ai_risks	factor	FALSE	1, 2. 2, 3. 3, 4. 4, 5. 5	601	0.72	5	4: 560, 3: 395, 5: 311, 2: 229	NA

prioritize_mental_health

Distribution

Distribution of values for prioritize_mental_health

641 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
prioritize_mental_health	factor	FALSE	1, 2. 2, 3. 3, 4. 4, 5. 5	641	0.7	5	3: 549, 2: 489, 4: 287, 1: 118	NA

prioritize_global_poverty

Distribution

Distribution of values for prioritize_global_poverty

539 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
prioritize_global_poverty	factor	FALSE	1, 2. 2, 3. 3, 4. 4, 5. 5	539	0.75	5	4: 603, 3: 412, 5: 374, 2: 208	NA

prioritize_meta

Distribution

Distribution of values for prioritize_meta

1107 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
prioritize_meta	factor	FALSE	1, 2. 2, 3. 3, 4. 4, 5. 5	1107	0.49	5	3: 366, 2: 363, 4: 206, 5: 62	NA

prioritize_ea_movement

Distribution

Distribution of values for prioritize_ea_movement

639 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
prioritize_ea_movement	factor	FALSE	1, 2. 2, 3. 3, 4. 4, 5. 5	639	0.7	5	3: 558, 4: 469, 2: 308, 5: 164	NA

prioritize_x_risks

Distribution

Distribution of values for prioritize_x_risks

678 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
prioritize_x_risks	factor	FALSE	1, 2. 2, 3. 3, 4. 4, 5. 5	678	0.69	5	3: 504, 4: 484, 2: 280, 5: 164	NA

prioritize_broad_longtermism

Distribution

Distribution of values for prioritize_broad_longtermism

758 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
prioritize_broad_longtermism	factor	FALSE	1, 2. 2, 3. 3, 4. 4, 5. 5	758	0.65	5	3: 445, 4: 390, 2: 359, 5: 142	NA

prioritize_other

Are there any other causes you feel should be priorities for the EA community?

Distribution

Distribution of values for prioritize_other

1697 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
prioritize_other	Are there any other causes you feel should be priorities for the EA community?	character	1697	0.22	458	0	2	608	0

currency

Distribution

Distribution of values for currency

555 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
currency	character	555	0.74	22	0	3	3	0	NA

currency_other

Please select the currency that pertains to you. Other

Distribution

Distribution of values for currency_other

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
currency_other	Please select the currency that pertains to you. Other	character	0	1	94	1961	0	37	0

income

What was your pre-tax individual income in 2019?

Distribution

Distribution of values for income

665 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
income	What was your pre-tax individual income in 2019?	numeric	665	0.69	0	35000	36000000	151598	1104476	▇▁▁▁▁

donation_2019

In 2019, roughly how much money did you donate?

Distribution

Distribution of values for donation_2019

647 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
donation_2019	In 2019, roughly how much money did you donate?	numeric	647	0.7	0	600	3e+06	12315	109658	▇▁▁▁▁

donation_2020

In 2020, how much do you currently plan to donate?

Distribution

Distribution of values for donation_2020

669 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
donation_2020	In 2020, how much do you currently plan to donate?	numeric	669	0.69	0	1200	3e+06	15640	113144	▇▁▁▁▁

donate_later

Are you presently saving money to donate later, rather than donate now?

Distribution

Distribution of values for donate_later

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
donate_later	Are you presently saving money to donate later, rather than donate now?	character	0	1	3	623	0	21	0

university_original

If applicable, which university or universities did you attend?

Distribution

Distribution of values for university_original

712 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
university_original	If applicable, which university or universities did you attend?	character	712	0.67	1079	0	1	141	0

birth_year

In which year were you born?

Distribution

Distribution of values for birth_year

505 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
birth_year	In which year were you born?	numeric	505	0.77	1918	1993	2016	1990	9.8	▁▁▁▇▃

gender_original

Gender, original

Distribution

Distribution of values for gender_original

526 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
gender_original	Gender, original	character	526	0.76	88	0	1	82	0

sexual_orientation

What is your sexual orientation?

Distribution

Distribution of values for sexual_orientation

686 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
sexual_orientation	What is your sexual orientation?	character	686	0.68	166	0	1	123	0

country

Distribution

Distribution of values for country

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
country	character	0	1	62	503	0	24	0	NA

city_other

In what town/city/metropolitan area do you live? Other

Distribution

Distribution of values for city_other

1296 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
city_other	In what town/city/metropolitan area do you live? Other	character	1296	0.4	465	0	2	88	0

ea_community_ideal

How well does the EA community compare to your ideal?

Distribution

Distribution of values for ea_community_ideal

617 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
ea_community_ideal	How well does the EA community compare to your ideal?	numeric	617	0.71	1	7	10	7	1.7	▁▁▃▇▂

ea_community_satisfaction

What is your overall satisfaction with the EA community?

Distribution

Distribution of values for ea_community_satisfaction

624 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
ea_community_satisfaction	What is your overall satisfaction with the EA community?	numeric	624	0.71	1	8	10	7.3	1.7	▁▁▃▇▃

ea_community_why

Why did you give the two ratings above? Open-Ended Response

Distribution

Distribution of values for ea_community_why

1101 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
ea_community_why	Why did you give the two ratings above? Open-Ended Response	character	1101	0.49	1062	0	6	2291	0

agree_ea_helps_impact

Agree: The EA community helps me have more impact.

Distribution

Distribution of values for agree_ea_helps_impact

603 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
agree_ea_helps_impact	Agree: The EA community helps me have more impact.	factor	FALSE	Strongly disagree, 2. (2) Disagree, 3. (3) Neither agree nor disagree, 4. (4) Agree, 5. (5) Strongly agree	603	0.72	5	(4): 634, (3): 413, (5): 355, (2): 105

agree_part_of_ea_community

Agree: I feel that I am a part of the effective altruism community.

Distribution

Distribution of values for agree_part_of_ea_community

584 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
agree_part_of_ea_community	Agree: I feel that I am a part of the effective altruism community.	factor	FALSE	Strongly disagree, 2. (2) Disagree, 3. (3) Neither agree nor disagree, 4. (4) Agree, 5. (5) Strongly agree	584	0.73	5	(4): 621, (5): 353, (3): 334, (2): 214

friend_introduce

How excited would you be to introduce a friend to the EA community?

Distribution

Distribution of values for friend_introduce

581 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
friend_introduce	How excited would you be to introduce a friend to the EA community?	numeric	581	0.73	1	8	10	7.7	2	▁▁▃▇▇

learned_80k

80,000 Hours - Changed mind or learned something important

Distribution

Distribution of values for learned_80k

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
learned_80k	80,000 Hours - Changed mind or learned something important	numeric	829	0.62	0	0	1	0.39	0.49	▇▁▁▁▅

connection_80k

80,000 Hours - New interesting and valuable connection

Distribution

Distribution of values for connection_80k

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
connection_80k	80,000 Hours - New interesting and valuable connection	numeric	829	0.62	0	0	1	0.09	0.28	▇▁▁▁▁

learned_ea_global

EA Global - Changed mind or learned something important

Distribution

Distribution of values for learned_ea_global

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
learned_ea_global	EA Global - Changed mind or learned something important	numeric	829	0.62	0	0	1	0.07	0.25	▇▁▁▁▁

connection_ea_global

EA Global - New interesting and valuable connection

Distribution

Distribution of values for connection_ea_global

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
connection_ea_global	EA Global - New interesting and valuable connection	numeric	829	0.62	0	0	1	0.11	0.31	▇▁▁▁▁

learned_ea_hub

EA Hub - Changed mind or learned something important

Distribution

Distribution of values for learned_ea_hub

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
learned_ea_hub	EA Hub - Changed mind or learned something important	numeric	829	0.62	0	0	1	0.02	0.14	▇▁▁▁▁

connection_ea_hub

EA Hub - New interesting and valuable connection

Distribution

Distribution of values for connection_ea_hub

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
connection_ea_hub	EA Hub - New interesting and valuable connection	numeric	829	0.62	0	0	1	0.02	0.14	▇▁▁▁▁

learned_ea_student_mentoring

EA Student Career Mentoring - Changed mind or learned something important

Distribution

Distribution of values for learned_ea_student_mentoring

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
learned_ea_student_mentoring	EA Student Career Mentoring - Changed mind or learned something important	numeric	829	0.62	0	0	1	0.03	0.16	▇▁▁▁▁

connection_ea_student_mentor

EA Student Career Mentoring - New interesting and valuable connection

Distribution

Distribution of values for connection_ea_student_mentor

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
connection_ea_student_mentor	EA Student Career Mentoring - New interesting and valuable connection	numeric	829	0.62	0	0	1	0.03	0.18	▇▁▁▁▁

learned_eagx

EAGx - Changed mind or learned something important

Distribution

Distribution of values for learned_eagx

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
learned_eagx	EAGx - Changed mind or learned something important	numeric	829	0.62	0	0	1	0.07	0.26	▇▁▁▁▁

connection_eagx

EAGx - New interesting and valuable connection

Distribution

Distribution of values for connection_eagx

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
connection_eagx	EAGx - New interesting and valuable connection	numeric	829	0.62	0	0	1	0.11	0.32	▇▁▁▁▁

learned_effective_thesis

Effective Thesis - Changed mind or learned something important

Distribution

Distribution of values for learned_effective_thesis

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
learned_effective_thesis	Effective Thesis - Changed mind or learned something important	numeric	829	0.62	0	0	1	0.02	0.15	▇▁▁▁▁

connection_effective_thesis

Effective Thesis - New interesting and valuable connection

Distribution

Distribution of values for connection_effective_thesis

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
connection_effective_thesis	Effective Thesis - New interesting and valuable connection	numeric	829	0.62	0	0	1	0.03	0.16	▇▁▁▁▁

learned_facebook_group

Facebook groups related to EA - Changed mind or learned something important

Distribution

Distribution of values for learned_facebook_group

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
learned_facebook_group	Facebook groups related to EA - Changed mind or learned something important	numeric	829	0.62	0	0	1	0.09	0.28	▇▁▁▁▁

connection_facebook_group

Facebook groups related to EA - New interesting and valuable connection

Distribution

Distribution of values for connection_facebook_group

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
connection_facebook_group	Facebook groups related to EA - New interesting and valuable connection	numeric	829	0.62	0	0	1	0.09	0.28	▇▁▁▁▁

learned_gwwc

Giving What We Can - Changed mind or learned something important

Distribution

Distribution of values for learned_gwwc

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
learned_gwwc	Giving What We Can - Changed mind or learned something important	numeric	829	0.62	0	0	1	0.07	0.25	▇▁▁▁▁

connection_gwwc

Giving What We Can - New interesting and valuable connection

Distribution

Distribution of values for connection_gwwc

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
connection_gwwc	Giving What We Can - New interesting and valuable connection	numeric	829	0.62	0	0	1	0.05	0.21	▇▁▁▁▁

learned_intl_ea_events

International EA social events - Changed mind or learned something important

Distribution

Distribution of values for learned_intl_ea_events

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
learned_intl_ea_events	International EA social events - Changed mind or learned something important	numeric	829	0.62	0	0	1	0.04	0.21	▇▁▁▁▁

connection_intl_ea_events

International EA social events - New interesting and valuable connection

Distribution

Distribution of values for connection_intl_ea_events

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
connection_intl_ea_events	International EA social events - New interesting and valuable connection	numeric	829	0.62	0	0	1	0.09	0.28	▇▁▁▁▁

learned_personal_connection

A personal connection - Changed mind or learned something important

Distribution

Distribution of values for learned_personal_connection

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
learned_personal_connection	A personal connection - Changed mind or learned something important	numeric	829	0.62	0	0	1	0.27	0.44	▇▁▁▁▃

connection_personal_contact

A personal connection - New interesting and valuable connection

Distribution

Distribution of values for connection_personal_contact

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
connection_personal_contact	A personal connection - New interesting and valuable connection	numeric	829	0.62	0	0	1	0.27	0.45	▇▁▁▁▃

learned_lesswrong

LessWrong - Changed mind or learned something important

Distribution

Distribution of values for learned_lesswrong

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
learned_lesswrong	LessWrong - Changed mind or learned something important	numeric	829	0.62	0	0	1	0.14	0.35	▇▁▁▁▂

connection_lesswrong

LessWrong - New interesting and valuable connection

Distribution

Distribution of values for connection_lesswrong

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
connection_lesswrong	LessWrong - New interesting and valuable connection	numeric	829	0.62	0	0	1	0.05	0.22	▇▁▁▁▁

learned_local_group

Local EA groups - Changed mind or learned something important

Distribution

Distribution of values for learned_local_group

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
learned_local_group	Local EA groups - Changed mind or learned something important	numeric	829	0.62	0	0	1	0.17	0.38	▇▁▁▁▂

connection_local_groups

Local EA groups - New interesting and valuable connection

Distribution

Distribution of values for connection_local_groups

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
connection_local_groups	Local EA groups - New interesting and valuable connection	numeric	829	0.62	0	0	1	0.27	0.45	▇▁▁▁▃

learned_non_local_group

Non-local meetups - Changed mind or learned something important

Distribution

Distribution of values for learned_non_local_group

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
learned_non_local_group	Non-local meetups - Changed mind or learned something important	numeric	829	0.62	0	0	1	0.02	0.16	▇▁▁▁▁

connection_non_local_group

Non-local meetups - New interesting and valuable connection

Distribution

Distribution of values for connection_non_local_group

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
connection_non_local_group	Non-local meetups - New interesting and valuable connection	numeric	829	0.62	0	0	1	0.05	0.22	▇▁▁▁▁

learned_ea_forum

The EA Forum - Changed mind or learned something important

Distribution

Distribution of values for learned_ea_forum

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
learned_ea_forum	The EA Forum - Changed mind or learned something important	numeric	829	0.62	0	0	1	0.19	0.4	▇▁▁▁▂

connection_ea_forum

The EA Forum - New interesting and valuable connection

Distribution

Distribution of values for connection_ea_forum

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
connection_ea_forum	The EA Forum - New interesting and valuable connection	numeric	829	0.62	0	0	1	0.06	0.23	▇▁▁▁▁

learned_ea_books

EA books - Changed mind or learned something important

Distribution

Distribution of values for learned_ea_books

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
learned_ea_books	EA books - Changed mind or learned something important	numeric	829	0.62	0	0	1	0.24	0.43	▇▁▁▁▂

connection_ea_books

EA books - New interesting and valuable connection

Distribution

Distribution of values for connection_ea_books

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
connection_ea_books	EA books - New interesting and valuable connection	numeric	829	0.62	0	0	1	0.05	0.23	▇▁▁▁▁

learned_ea_newsletter

The EA Newsletter - Changed mind or learned something important

Distribution

Distribution of values for learned_ea_newsletter

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
learned_ea_newsletter	The EA Newsletter - Changed mind or learned something important	numeric	829	0.62	0	0	1	0.09	0.29	▇▁▁▁▁

connection_ea_newsletter

The EA Newsletter - New interesting and valuable connection

Distribution

Distribution of values for connection_ea_newsletter

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
connection_ea_newsletter	The EA Newsletter - New interesting and valuable connection	numeric	829	0.62	0	0	1	0.04	0.2	▇▁▁▁▁

learned_none

None of the above - Changed mind or learned something important

Distribution

Distribution of values for learned_none

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
learned_none	None of the above - Changed mind or learned something important	numeric	829	0.62	0	0	1	0.08	0.28	▇▁▁▁▁

connection_none

None of the above - New interesting and valuable connection

Distribution

Distribution of values for connection_none

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
connection_none	None of the above - New interesting and valuable connection	numeric	829	0.62	0	0	1	0.09	0.29	▇▁▁▁▁

learned_connection_other

Other (please specify)

Distribution

Distribution of values for learned_connection_other

829 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
learned_connection_other	Other (please specify)	numeric	829	0.62	0	0	1	0.08	0.28	▇▁▁▁▁

participate_doing_good_better

Interested in: A reading group to discuss Doing Good Better

Distribution

Distribution of values for participate_doing_good_better

1941 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
participate_doing_good_better	Interested in: A reading group to discuss Doing Good Better	numeric	1941	0.1	1	1	1	1	0	▁▁▇▁▁

participate_the_precipice

Interested in: A reading group to discuss The Precipice

Distribution

Distribution of values for participate_the_precipice

1847 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
participate_the_precipice	Interested in: A reading group to discuss The Precipice	numeric	1847	0.15	1	1	1	1	0	▁▁▇▁▁

participate_fellowship_intro

Interested in: A fellowship covering the basics of effective altruism

Distribution

Distribution of values for participate_fellowship_intro

1973 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
participate_fellowship_intro	Interested in: A fellowship covering the basics of effective altruism	numeric	1973	0.09	1	1	1	1	0	▁▁▇▁▁

participate_fellowship_adv

Interested in: A fellowship covering advanced principles of effective altruism

Distribution

Distribution of values for participate_fellowship_adv

1702 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
participate_fellowship_adv	Interested in: A fellowship covering advanced principles of effective altruism	numeric	1702	0.21	1	1	1	1	0	▁▁▇▁▁

participate_80k_pod_discuss

Interested in: An 80,000 Hours podcast discussion group

Distribution

Distribution of values for participate_80k_pod_discuss

1901 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
participate_80k_pod_discuss	Interested in: An 80,000 Hours podcast discussion group	numeric	1901	0.12	1	1	1	1	0	▁▁▇▁▁

participate_fellowship_career

Interested in: A 4-part fellowship using the 80k tool for career planning

Distribution

Distribution of values for participate_fellowship_career

1735 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
participate_fellowship_career	Interested in: A 4-part fellowship using the 80k tool for career planning	numeric	1735	0.2	1	1	1	1	0	▁▁▇▁▁

participate_fellowship_causes

Interested in: A fellowship covering key ideas related to your top cause area

Distribution

Distribution of values for participate_fellowship_causes

1694 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
participate_fellowship_causes	Interested in: A fellowship covering key ideas related to your top cause area	numeric	1694	0.22	1	1	1	1	0	▁▁▇▁▁

participate_intro_one_on_one

Interested in: An introductory 1-on-1 convo to discuss the basic ideas of EA

Distribution

Distribution of values for participate_intro_one_on_one

2030 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
participate_intro_one_on_one	Interested in: An introductory 1-on-1 convo to discuss the basic ideas of EA	numeric	2030	0.06	1	1	1	1	0	▁▁▇▁▁

participate_gwwc_info_session

Interested in: A one-time information session about GWWC / Try Giving

Distribution

Distribution of values for participate_gwwc_info_session

2019 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
participate_gwwc_info_session	Interested in: A one-time information session about GWWC / Try Giving	numeric	2019	0.07	1	1	1	1	0	▁▁▇▁▁

participate_donation_discuss

Interested in: A one-time discussion about where other EAs are donating

Distribution

Distribution of values for participate_donation_discuss

1854 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
participate_donation_discuss	Interested in: A one-time discussion about where other EAs are donating	numeric	1854	0.14	1	1	1	1	0	▁▁▇▁▁

participate_social_event

Interested in: A one-time (virtual) social event to meet local EAs

Distribution

Distribution of values for participate_social_event

1721 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
participate_social_event	Interested in: A one-time (virtual) social event to meet local EAs	numeric	1721	0.2	1	1	1	1	0	▁▁▇▁▁

participate_contact

May we (CEA) contact you if the activit(ies) you selected become(s) available?

Distribution

Distribution of values for participate_contact

765 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
participate_contact	May we (CEA) contact you if the activit(ies) you selected become(s) available?	numeric	765	0.65	1	1	1	1	0	▁▁▇▁▁

email_next_survey

Please send me an e-mail to next year’s survey

Distribution

Distribution of values for email_next_survey

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
email_next_survey	Please send me an e-mail to next year’s survey	character	0	1	2	868	0	46	0

email_followup_surveys

Please e-mail me relevant followup surveys

Distribution

Distribution of values for email_followup_surveys

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
email_followup_surveys	Please e-mail me relevant followup surveys	character	0	1	2	1289	0	42	0

email_dont_email

Don’t e-mail me about future surveys

Distribution

Distribution of values for email_dont_email

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
email_dont_email	Don’t e-mail me about future surveys	character	0	1	2	2054	0	36	0

share_80k

Yes - I give my permission for this information to be shared with 80,000 Hours

Distribution

Distribution of values for share_80k

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
share_80k	Yes - I give my permission for this information to be shared with 80,000 Hours	character	0	1	2	928	0	78	0

dont_share_80k

No - I do not wish for any of my information to be shared with 80,000 Hours

Distribution

Distribution of values for dont_share_80k

1893 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
dont_share_80k	No - I do not wish for any of my information to be shared with 80,000 Hours	character	1893	0.13	1	0	149	149	0

profile_ea_hub

Would you like a personal profile on the EA Hub?

Distribution

Distribution of values for profile_ea_hub

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
profile_ea_hub	Would you like a personal profile on the EA Hub?	character	0	1	3	644	0	91	0

agree_quantify_compare_impact

Agree: It’s possible to roughly quantify and compare different types of impact

Distribution

Distribution of values for agree_quantify_compare_impact

1119 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
agree_quantify_compare_impact	Agree: It’s possible to roughly quantify and compare different types of impact	factor	FALSE	Strongly disagree, 2. (2) Disagree, 3. (3) Slightly disagree, 4. (4) Neither agree nor disagree, 5. (5) Slightly agree, 6. (6) Agree, 7. (7) Strongly agree	1119	0.48	6	(6): 505, (7): 354, (5): 150, (4): 16

agree_ways_better_than_others

Agree: Some ways of doing good are substantially better than others

Distribution

Distribution of values for agree_ways_better_than_others

1117 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
agree_ways_better_than_others	Agree: Some ways of doing good are substantially better than others	factor	FALSE	Strongly disagree, 2. (2) Disagree, 3. (3) Slightly disagree, 4. (4) Neither agree nor disagree, 5. (5) Slightly agree, 6. (6) Agree, 7. (7) Strongly agree	1117	0.48	5	(7): 803, (6): 204, (5): 28, (4): 9

agree_work_on_any_cause

Agree: It makes sense to be open to working on any cause

Distribution

Distribution of values for agree_work_on_any_cause

1122 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
agree_work_on_any_cause	Agree: It makes sense to be open to working on any cause	factor	FALSE	Strongly disagree, 2. (2) Disagree, 3. (3) Slightly disagree, 4. (4) Neither agree nor disagree, 5. (5) Slightly agree, 6. (6) Agree, 7. (7) Strongly agree	1122	0.48	7	(6): 371, (7): 370, (5): 156, (3): 57

agree_farmed_animals_concern

Agree: Farmed animals deserve our moral concern

Distribution

Distribution of values for agree_farmed_animals_concern

1114 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
agree_farmed_animals_concern	Agree: Farmed animals deserve our moral concern	factor	FALSE	Strongly disagree, 2. (2) Disagree, 3. (3) Slightly disagree, 4. (4) Neither agree nor disagree, 5. (5) Slightly agree, 6. (6) Agree, 7. (7) Strongly agree	1114	0.49	7	(7): 603, (6): 263, (5): 117, (4): 30

agree_longtermism

Agree: The impact of our actions on the very long-term future is most important

Distribution

Distribution of values for agree_longtermism

1117 missing values.

Summary statistics

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
agree_longtermism	Agree: The impact of our actions on the very long-term future is most important	factor	FALSE	Strongly disagree, 2. (2) Disagree, 3. (3) Slightly disagree, 4. (4) Neither agree nor disagree, 5. (5) Slightly agree, 6. (6) Agree, 7. (7) Strongly agree	1117	0.48	7	(6): 263, (5): 242, (7): 213, (4): 143

reputation_effect_explanation

If possible, could you please explain your answer?

Distribution

Distribution of values for reputation_effect_explanation

1668 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
reputation_effect_explanation	If possible, could you please explain your answer?	character	1668	0.23	496	0	3	1336	0

bottleneck_productivity

Are there any things which you think currently bottleneck your positive impact?

Distribution

Distribution of values for bottleneck_productivity

1627 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
bottleneck_productivity	Are there any things which you think currently bottleneck your positive impact?	character	1627	0.25	530	0	2	1200	0

dislike_ea_community

What do you personally dislike about the EA community and EA/EA-adjacent ideas?

Distribution

Distribution of values for dislike_ea_community

1611 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
dislike_ea_community	What do you personally dislike about the EA community and EA/EA-adjacent ideas?	character	1611	0.26	545	0	1	2668	0

donate_rethink_charity

Roughly how much did you donate in 2019? Rethink Charity

Distribution

Distribution of values for donate_rethink_charity

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
donate_rethink_charity	Roughly how much did you donate in 2019? Rethink Charity	character	0	1	13	2013	0	33	0

donate_80k

Roughly how much did you donate in 2019? 80,000 Hours

Distribution

Distribution of values for donate_80k

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
donate_80k	Roughly how much did you donate in 2019? 80,000 Hours	character	0	1	10	2018	0	5	0

donate_center_applied_rational

Roughly how much did you donate in 2019? Center For Applied Rationality

Distribution

Distribution of values for donate_center_applied_rational

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
donate_center_applied_rational	Roughly how much did you donate in 2019? Center For Applied Rationality	character	0	1	4	2023	0	3	0

donate_mercy_for_animals

Roughly how much did you donate in 2019? Mercy For Animals

Distribution

Distribution of values for donate_mercy_for_animals

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
donate_mercy_for_animals	Roughly how much did you donate in 2019? Mercy For Animals	character	0	1	15	2012	0	19	0

donate_other1

Roughly how much did you donate in 2019? Other (please specify)

Distribution

Distribution of values for donate_other1

1912 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
donate_other1	Roughly how much did you donate in 2019? Other (please specify)	character	1912	0.12	229	0	1	315	0

donate_other2

Roughly how much did you donate in 2019? Other 2 (please specify)

Distribution

Distribution of values for donate_other2

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
donate_other2	Roughly how much did you donate in 2019? Other 2 (please specify)	character	0	1	104	2042	0	74	0

donate_other3

Roughly how much did you donate in 2019? Other 3 (please specify)

Distribution

Distribution of values for donate_other3

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
donate_other3	Roughly how much did you donate in 2019? Other 3 (please specify)	character	0	1	61	2086	0	62	0

donate_other4

Roughly how much did you donate in 2019? Other 4 (please specify)

Distribution

Distribution of values for donate_other4

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
donate_other4	Roughly how much did you donate in 2019? Other 4 (please specify)	character	0	1	34	2114	0	74	0

donate_other5

Roughly how much did you donate in 2019? Other 5 (please specify)

Distribution

Distribution of values for donate_other5

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
donate_other5	Roughly how much did you donate in 2019? Other 5 (please specify)	character	0	1	17	2131	0	61	0

datecreated

Date Created

Distribution

Distribution of values for datecreated

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
datecreated	Date Created	character	0	1	22	0	22	22	0

group_name_original

Distribution

Distribution of values for group_name_original

1294 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
group_name_original		character	1294	0.4	442	0	5	324	0

group_name_manual

Group Name, manually assigned

Distribution

Distribution of values for group_name_manual

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
group_name_manual	Group Name, manually assigned	character	0	1	213	1296	0	66	0

first_hear_qual

Distribution

Distribution of values for first_hear_qual

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
first_hear_qual		character	0	1	127	1004	0	21	0

_merge {#_merge .tabset}

Distribution {#_merge_distribution}

Distribution of values for _merge

0 missing values.

Summary statistics {#_merge_summary}

name	label	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts
_merge		factor	FALSE	master only (1), 2. using only (2), 3. matched (3), 4. missing updated (4), 5. nonmissing conflict (5)	0	1	1	mat: 2164, mas: 0, usi: 0, mis: 0

ea_id

Distribution

Distribution of values for ea_id

1937 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
ea_id	character	1937	0.1	227	0	32	32	0	NA

ea_id2

Distribution

Distribution of values for ea_id2

175 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
ea_id2	character	175	0.92	1932	0	32	32	0	NA

ea_id3

Distribution

Distribution of values for ea_id3

1954 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
ea_id3	character	1954	0.1	210	0	32	32	0	NA

engagement

Distribution

Distribution of values for engagement

259 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
engagement	factor	FALSE	No engagement, 2. (2) Mild engagement, 3. (3) Moderate engagement, 4. (4) Considerable engagement, 5. (5) High engagement	259	0.88	5	(3): 569, (4): 561, (5): 371, (2): 359	NA

capital_over_impact

Distribution

Distribution of values for capital_over_impact

496 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
capital_over_impact	factor	FALSE	Modestly prioritizing career capital, 2. Modestly prioritizing immediate impact, 3. N/A, 4. Prioritizing both equally, 5. Strongly prioritizing career capital, 6. Strongly prioritizing immediate impact	496	0.77	6	Str: 438, Mod: 424, Pri: 279, Mod: 243	NA

financial_instability

Distribution

Distribution of values for financial_instability

493 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
financial_instability	factor	FALSE	Always, 2. Never, 3. Often, 4. Prefer not to answer, 5. Rarely, 6. Sometimes	493	0.77	6	Nev: 753, Rar: 393, Som: 300, Oft: 136	NA

first_generation_student

Distribution

Distribution of values for first_generation_student

492 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
first_generation_student	factor	FALSE	No, 2. Yes	492	0.77	2	No: 1384, Yes: 288	NA

reputation_effect

Distribution

Distribution of values for reputation_effect

1169 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
reputation_effect	factor	FALSE	No, no reputational consequences at all, 2. Yes, a mix of reputational benefits and negative reputational costs, 3. Yes, mostly negative reputational costs, 4. Yes, mostly positive reputational benefits	1169	0.46	4	No,: 442, Yes: 307, Yes: 200, Yes: 46	NA

year_involved

Distribution

Distribution of values for year_involved

270 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
year_involved	factor	FALSE	2009 or before, 2. 2010, 3. 2011, 4. 2012, 5. 2013, 6. 2014, 7. 2015, 8. 2016, 9. 2017, 10. 2018, 11. 2019, 12. 2020, 13. I don’t remember	270	0.88	13	202: 329, 201: 292, 201: 261, 201: 254	NA

first_hear_ea

Distribution

Distribution of values for first_hear_ea

254 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
first_hear_ea	factor	FALSE	I don’t remember, 2. 80,000 Hours, 3. Animal Charity Evaluators, 4. Book, article, or blog post, 5. EA Global / EAGx, 6. Educational course (e.g. lecture, class, MOOC), 7. Facebook, 8. GiveWell, 9. Giving What We Can, 10. LessWrong, 11. Local or university EA group, 12. One For The World, 13. Other, 14. Personal contact (e.g. friend, colleague, relative), 15. Podcast, 16. REG / EAF / FRI / The Swiss group, 17. Search engine, 18. Slate Star Codex, 19. TED talk, 20. The Life You Can Save (organization), 21. Vox’s Future Perfect	254	0.88	21	Per: 310, 80,: 244, Boo: 179, Oth: 167	NA

city

Distribution

Distribution of values for city

562 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
city	factor	FALSE	Amsterdam, 2. Auckland, 3. Berlin, 4. Boston / Cambridge (USA), 5. Cambridge (UK), 6. Canberra, 7. Chicago, 8. London, 9. Los Angeles, 10. Melbourne, 11. New York City, 12. Oslo, 13. Other (please specify), 14. Oxford, 15. Philadelphia, 16. SF Bay Area, 17. Seattle, 18. Stockholm, 19. Sydney, 20. Toronto, 21. Vienna, 22. Washington, DC, 23. Zürich	562	0.74	23	Oth: 868, SF : 100, Lon: 90, New: 77	NA

collector_source

Distribution

Distribution of values for collector_source

0 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
collector_source	factor	FALSE	80K 2, 2. 80K1, 3. CE, 4. CEA FB, 5. EA FB, 6. EA Forum, 7. EA Forum backup, 8. EA Newsletter, 9. EAA newsletter?, 10. EAS80K3, 11. Email Invitation 1, 12. GWWC, 13. Groups FB, 14. Groups newsletter?, 15. Groups personal email?, 16. Groups slack, 17. Hangouts, 18. LG Newsletter, 19. LW, 20. Reddit, 21. SSC, 22. Sharing, 23. dankeamemes	0	1	23	EA : 426, 80K: 409, Ema: 227, EA : 220	NA

gender_manual

Distribution

Distribution of values for gender_manual

536 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
gender_manual	factor	FALSE	Other, 2. Female, 3. Male	536	0.75	3	Mal: 1148, Fem: 438, Oth: 42	NA

race_white

What is your race/ethnicity? White

Distribution

Distribution of values for race_white

507 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
race_white	What is your race/ethnicity? White	numeric	507	0.77	0	1	1	0.83	0.38	▂▁▁▁▇

race_black_aa

What is your race/ethnicity? Black or African American

Distribution

Distribution of values for race_black_aa

507 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
race_black_aa	What is your race/ethnicity? Black or African American	numeric	507	0.77	0	0	1	0.01	0.12	▇▁▁▁▁

race_hispanic_la_spanish

What is your race/ethnicity? Hispanic, Latino or Spanish Origin

Distribution

Distribution of values for race_hispanic_la_spanish

507 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
race_hispanic_la_spanish	What is your race/ethnicity? Hispanic, Latino or Spanish Origin	numeric	507	0.77	0	0	1	0.04	0.2	▇▁▁▁▁

race_american_indian_alaskan

What is your race/ethnicity? American Indian or Alaskan Native

Distribution

Distribution of values for race_american_indian_alaskan

507 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
race_american_indian_alaskan	What is your race/ethnicity? American Indian or Alaskan Native	numeric	507	0.77	0	0	1	0	0.04	▇▁▁▁▁

race_asian

What is your race/ethnicity? Asian

Distribution

Distribution of values for race_asian

507 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
race_asian	What is your race/ethnicity? Asian	numeric	507	0.77	0	0	1	0.12	0.33	▇▁▁▁▁

race_native_hawaiin_pacific

What is your race/ethnicity? Native Hawaiian or Other Pacific Islander

Distribution

Distribution of values for race_native_hawaiin_pacific

507 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
race_native_hawaiin_pacific	What is your race/ethnicity? Native Hawaiian or Other Pacific Islander	numeric	507	0.77	0	0	1	0	0.05	▇▁▁▁▁

race_prefer_no_answer

What is your race/ethnicity? Prefer not to answer

Distribution

Distribution of values for race_prefer_no_answer

507 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
race_prefer_no_answer	What is your race/ethnicity? Prefer not to answer	numeric	507	0.77	0	0	1	0.03	0.16	▇▁▁▁▁

race_other

What is your race/ethnicity? Other (please specify)

Distribution

Distribution of values for race_other

507 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
race_other	What is your race/ethnicity? Other (please specify)	numeric	507	0.77	0	0	1	0.04	0.2	▇▁▁▁▁

race_

Distribution

Distribution of values for race_

507 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
race_	factor	FALSE	american_indian_alaskan, 2. asian, 3. black_aa, 4. hispanic_la_spanish, 5. native_hawaiin_pacific, 6. other, 7. prefer_no_answer, 8. white	507	0.77	8	whi: 1260, asi: 203, oth: 68, his: 59	NA

status_employed_ft

Employment/student status? Employed, full-time

Distribution

Distribution of values for status_employed_ft

472 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
status_employed_ft	Employment/student status? Employed, full-time	numeric	472	0.78	0	0	1	0.49	0.5	▇▁▁▁▇

status_employed_pt

Employment/student status? Employed, part time

Distribution

Distribution of values for status_employed_pt

472 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
status_employed_pt	Employment/student status? Employed, part time	numeric	472	0.78	0	0	1	0.11	0.31	▇▁▁▁▁

status_self_employed

Employment/student status? Self-employed

Distribution

Distribution of values for status_self_employed

472 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
status_self_employed	Employment/student status? Self-employed	numeric	472	0.78	0	0	1	0.11	0.31	▇▁▁▁▁

status_not_employed_looking

Employment/student status? Not employed, but looking

Distribution

Distribution of values for status_not_employed_looking

472 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
status_not_employed_looking	Employment/student status? Not employed, but looking	numeric	472	0.78	0	0	1	0.06	0.24	▇▁▁▁▁

status_not_employed

Employment/student status? Not employed, but not looking

Distribution

Distribution of values for status_not_employed

472 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
status_not_employed	Employment/student status? Not employed, but not looking	numeric	472	0.78	0	0	1	0.02	0.16	▇▁▁▁▁

status_homemaker_parent

Employment/student status? Homemaker / full-time parent

Distribution

Distribution of values for status_homemaker_parent

472 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
status_homemaker_parent	Employment/student status? Homemaker / full-time parent	numeric	472	0.78	0	0	1	0.01	0.08	▇▁▁▁▁

status_retired

Employment/student status? Retired

Distribution

Distribution of values for status_retired

472 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
status_retired	Employment/student status? Retired	numeric	472	0.78	0	0	1	0.02	0.15	▇▁▁▁▁

status_student_hs

Employment/student status? Student (high school)

Distribution

Distribution of values for status_student_hs

472 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
status_student_hs	Employment/student status? Student (high school)	numeric	472	0.78	0	0	1	0.01	0.1	▇▁▁▁▁

status_student_undergrad

Employment/student status? Student (undergraduate)

Distribution

Distribution of values for status_student_undergrad

472 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
status_student_undergrad	Employment/student status? Student (undergraduate)	numeric	472	0.78	0	0	1	0.18	0.38	▇▁▁▁▂

status_student_masters

Employment/student status? Student (masters or equivalent)

Distribution

Distribution of values for status_student_masters

472 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
status_student_masters	Employment/student status? Student (masters or equivalent)	numeric	472	0.78	0	0	1	0.1	0.29	▇▁▁▁▁

status_student_doctoral

Employment/student status? Student (doctoral degree or equivalent)

Distribution

Distribution of values for status_student_doctoral

472 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
status_student_doctoral	Employment/student status? Student (doctoral degree or equivalent)	numeric	472	0.78	0	0	1	0.07	0.26	▇▁▁▁▁

status_student_other

Employment/student status? Student (other)

Distribution

Distribution of values for status_student_other

472 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
status_student_other	Employment/student status? Student (other)	numeric	472	0.78	0	0	1	0.02	0.14	▇▁▁▁▁

status_prefer_no_answer

Employment/student status? Prefer not to answer

Distribution

Distribution of values for status_prefer_no_answer

472 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
status_prefer_no_answer	Employment/student status? Prefer not to answer	numeric	472	0.78	0	0	1	0	0.06	▇▁▁▁▁

status_

Distribution

Distribution of values for status_

472 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
status_	factor	FALSE	employed_ft, 2. employed_pt, 3. homemaker_parent, 4. not_employed, 5. not_employed_looking, 6. prefer_no_answer, 7. retired, 8. self_employed, 9. student_doctoral, 10. student_hs, 11. student_masters, 12. student_other, 13. student_undergrad	472	0.78	13	emp: 734, stu: 293, stu: 158, sel: 131	NA

career_still_deciding

Current career description? Still deciding what to pursue

Distribution

Distribution of values for career_still_deciding

487 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
career_still_deciding	Current career description? Still deciding what to pursue	numeric	487	0.77	0	0	1	0.27	0.44	▇▁▁▁▃

career_building_capital

Current career description? Building flexible career capital

Distribution

Distribution of values for career_building_capital

487 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
career_building_capital	Current career description? Building flexible career capital	numeric	487	0.77	0	0	1	0.29	0.45	▇▁▁▁▃

career_non_profit_ea

Current career description? Work at a non-profit (EA organization)

Distribution

Distribution of values for career_non_profit_ea

487 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
career_non_profit_ea	Current career description? Work at a non-profit (EA organization)	numeric	487	0.77	0	0	1	0.14	0.34	▇▁▁▁▁

career_non_profit

Current career description? Work at a non-profit (not an EA organization)

Distribution

Distribution of values for career_non_profit

487 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
career_non_profit	Current career description? Work at a non-profit (not an EA organization)	numeric	487	0.77	0	0	1	0.06	0.24	▇▁▁▁▁

career_for_profit_earn_to_give

Current career description? For profit (earning to give)

Distribution

Distribution of values for career_for_profit_earn_to_give

487 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
career_for_profit_earn_to_give	Current career description? For profit (earning to give)	numeric	487	0.77	0	0	1	0.19	0.39	▇▁▁▁▂

career_for_profit

Current career description? For profit (not earning to give)

Distribution

Distribution of values for career_for_profit

487 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
career_for_profit	Current career description? For profit (not earning to give)	numeric	487	0.77	0	0	1	0.13	0.34	▇▁▁▁▁

career_academia

Current career description? Academia

Distribution

Distribution of values for career_academia

487 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
career_academia	Current career description? Academia	numeric	487	0.77	0	0	1	0.18	0.39	▇▁▁▁▂

career_government

Current career description? Government

Distribution

Distribution of values for career_government

487 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
career_government	Current career description? Government	numeric	487	0.77	0	0	1	0.09	0.28	▇▁▁▁▁

career_think_tank_lobby

Current career description? Think tanks / lobbying / advocacy

Distribution

Distribution of values for career_think_tank_lobby

487 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
career_think_tank_lobby	Current career description? Think tanks / lobbying / advocacy	numeric	487	0.77	0	0	1	0.06	0.24	▇▁▁▁▁

career_na

Current career description? N/A

Distribution

Distribution of values for career_na

487 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
career_na	Current career description? N/A	numeric	487	0.77	0	0	1	0.03	0.18	▇▁▁▁▁

career_other

Current career description? Other

Distribution

Distribution of values for career_other

487 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
career_other	Current career description? Other	numeric	487	0.77	0	0	1	0.1	0.3	▇▁▁▁▁

career_

Distribution

Distribution of values for career_

487 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
career_	factor	FALSE	academia, 2. building_capital, 3. for_profit, 4. for_profit_earn_to_give, 5. government, 6. na, 7. non_profit, 8. non_profit_ea, 9. other, 10. still_deciding, 11. think_tank_lobby	487	0.77	11	aca: 250, for: 246, bui: 209, for: 188	NA

race

Distribution

Distribution of values for race

507 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
race	character	507	0.77	7	0	5	19	0	NA

age_approx

In which year were you born?

Distribution

Distribution of values for age_approx

505 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
age_approx	In which year were you born?	numeric	505	0.77	4	27	102	30	9.8	▃▇▁▁▁

employ_status

Distribution

Distribution of values for employ_status

472 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
employ_status	factor	FALSE	Employed (FT or self), 2. Other (pt, unemployed, retired, homemaker, declined), 3. Student	472	0.78	3	Emp: 865, Stu: 621, Oth: 206	NA

age_approx_ranges

Distribution

Distribution of values for age_approx_ranges

505 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
age_approx_ranges	factor	FALSE	[4, 23), 2. [23, 26), 3. [26, 29), 4. [29, 34), 5. [34, 120)	505	0.77	5	[29: 396, [34: 345, [4,: 328, [23: 302	NA

age_approx_split

Distribution

Distribution of values for age_approx_split

505 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
age_approx_split	factor	FALSE	[4, 27), 2. [27, 120)	505	0.77	2	[27: 916, [4,: 743	NA

engagement_num

Distribution

Distribution of values for engagement_num

259 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
engagement_num	numeric	259	0.88	1	3	5	3.5	1.1	▁▅▇▇▅	NA

engagement_f

Distribution

Distribution of values for engagement_f

259 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
engagement_f	factor	FALSE	No engagement, 2. (2) Mild engagement, 3. (3) Moderate engagement, 4. (4) Considerable engagement, 5. (5) High engagement	259	0.88	5	(3): 569, (4): 561, (5): 371, (2): 359	NA

d_engage_3_5

Distribution

Distribution of values for d_engage_3_5

259 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	count	mean	label
d_engage_3_5	logical	259	0.88	TRU: 1501, FAL: 404	0.79	NA

d_engage_4_5

Distribution

Distribution of values for d_engage_4_5

259 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	count	mean	label
d_engage_4_5	logical	259	0.88	FAL: 973, TRU: 932	0.49	NA

d_engage_5

Distribution

Distribution of values for d_engage_5

259 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	count	mean	label
d_engage_5	logical	259	0.88	FAL: 1534, TRU: 371	0.19	NA

income_k

Distribution

Distribution of values for income_k

665 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
income_k	numeric	665	0.69	0	35	36000	152	1104	▇▁▁▁▁	NA

d_male

Distribution

Distribution of values for d_male

536 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
d_male	numeric	536	0.75	0	1	1	0.71	0.46	▃▁▁▁▇	NA

d_student

Distribution

Distribution of values for d_student

472 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
d_student	numeric	472	0.78	0	0	1	0.37	0.48	▇▁▁▁▅	NA

d_live_usa

Distribution

Distribution of values for d_live_usa

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
d_live_usa	numeric	0	1	0	0	1	0.3	0.46	▇▁▁▁▃	NA

prioritize_lt

Distribution

Distribution of values for prioritize_lt

908 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
prioritize_lt	numeric	908	0.58	1	3.4	5	3.3	0.69	▁▃▇▇▁	NA

referrer

Distribution

Distribution of values for referrer

0 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
referrer	factor	FALSE	80K hours, 2. CEA FB, 3. dankeamemes, 4. EA FB, 5. EA Forum, 6. EA Newsletter, 7. Email; opt-in from prev. EAS, 8. Giving What We Can, 9. Groups FB, 10. Groups personal email, 11. Groups slack, 12. Less Wrong, 13. Reddit, 14. Shared link, 15. SlateStarCodex (Reddit group), 16. Other	0	1	16	80K: 488, EA : 427, Ema: 227, EA : 220	NA

referrer_cat

Distribution

Distribution of values for referrer_cat

0 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
referrer_cat	factor	FALSE	80K hours, 2. EA Forum, 3. EA Newsletter, 4. Email; opt-in from prev. EAS, 5. Giving What We Can, 6. Groups (local), 7. Less Wrong or SlateStarCodex-Reddit, 8. Reddit, 9. Shared link, 10. Social media (FB/memes), 11. Other	0	1	11	80K: 488, EA : 427, Gro: 334, Ema: 227	NA

referrer_min100

Distribution

Distribution of values for referrer_min100

0 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
referrer_min100	factor	FALSE	80K hours, 2. EA Forum, 3. EA Newsletter, 4. Email; opt-in from prev. EAS, 5. Groups personal email, 6. Groups slack, 7. Shared link, 8. Other	0	1	8	80K: 488, EA : 427, Oth: 278, Ema: 227	NA

referrer_cat2

Distribution

Distribution of values for referrer_cat2

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
referrer_cat2	character	0	1	5	0	5	24	0	NA

referrer_cat3

Distribution

Distribution of values for referrer_cat3

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
referrer_cat3	character	0	1	5	0	5	30	0	NA

engage_cats_1

Distribution

Distribution of values for engage_cats_1

259 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
engage_cats_1	character	259	0.88	4	0	1	3	0	NA

engage_cats_2

Distribution

Distribution of values for engage_cats_2

259 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
engage_cats_2	character	259	0.88	3	0	1	3	0	NA

start_date_quantiles

Distribution

Distribution of values for start_date_quantiles

0 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
start_date_quantiles	factor	FALSE	[0%, 20%), 2. [20%, 40%], 3. (40%, 60%], 4. (60%, 80%], 5. (80%, 100%]	0	1	5	(60: 540, [20: 461, (40: 429, [0%: 416	NA

start_date_thirds_by_referrer

Distribution

Distribution of values for start_date_thirds_by_referrer

0 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
start_date_thirds_by_referrer	factor	FALSE	[0%, 33.33%), 2. [33.33%, 66.67%], 3. (66.67%, 100%]	0	1	3	[33: 1004, (66: 641, [0%: 519	NA

survey_willing

Distribution

Distribution of values for survey_willing

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace	label
survey_willing	character	0	1	3	0	11	29	0	NA

donation_2019_c

Distribution

Distribution of values for donation_2019_c

697 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
donation_2019_c	numeric	697	0.68	0	528	2500000	7401	71727	▇▁▁▁▁	NA

donation_2020_c

Distribution

Distribution of values for donation_2020_c

718 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
donation_2020_c	numeric	718	0.67	0	1003	2e+06	9836	73044	▇▁▁▁▁	NA

income_c

Distribution

Distribution of values for income_c

713 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
income_c	numeric	713	0.67	0	33000	3e+06	60469	135751	▇▁▁▁▁	NA

income_k_c

Distribution

Distribution of values for income_k_c

713 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
income_k_c	numeric	713	0.67	0	33	3000	60	136	▇▁▁▁▁	NA

income_c_imp

Distribution

Distribution of values for income_c_imp

40 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
income_c_imp	numeric	40	0.98	1.9	39600	3e+06	55887	112726	▇▁▁▁▁	NA

don_share_inc_19

Distribution

Distribution of values for don_share_inc_19

794 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	hist	label
don_share_inc_19	numeric	794	0.63	0	0.03	Inf	Inf	▇▁▁▁▁	NA

don_share_inc_19_imp

Distribution

Distribution of values for don_share_inc_19_imp

708 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
don_share_inc_19_imp	numeric	708	0.67	0	0.022	67	0.13	1.8	▇▁▁▁▁	NA

don_19_p1

Distribution

Distribution of values for don_19_p1

697 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
don_19_p1	numeric	697	0.68	1	529	2500001	7402	71727	▇▁▁▁▁	NA

income_c_imp_k

Distribution

Distribution of values for income_c_imp_k

40 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
income_c_imp_k	numeric	40	0.98	0.0019	40	3000	56	113	▇▁▁▁▁	NA

action_gwwc_f

Distribution

Distribution of values for action_gwwc_f

0 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
action_gwwc_f	factor	FALSE	0, 2. 1	0	1	2	0: 1594, 1: 570	NA

top_priority_rating

Distribution

Distribution of values for top_priority_rating

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	hist	label
top_priority_rating	numeric	0	1	-Inf	5	5	-Inf	▁▁▁▃▇	NA

avg_priority_rating

Distribution

Distribution of values for avg_priority_rating

491 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
avg_priority_rating	numeric	491	0.77	1.7	3.2	5	3.3	0.49	▁▅▇▂▁	NA

mn_priority_rating

Distribution

Distribution of values for mn_priority_rating

491 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
mn_priority_rating	numeric	491	0.77	1.7	3.2	5	3.3	0.49	▁▅▇▂▁	NA

lt_top_priority

Distribution

Distribution of values for lt_top_priority

491 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	count	mean	label
lt_top_priority	logical	491	0.77	TRU: 852, FAL: 821	0.51	NA

lt_above_mn_priority

Distribution

Distribution of values for lt_above_mn_priority

524 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	count	mean	label
lt_above_mn_priority	logical	524	0.76	TRU: 825, FAL: 815	0.5	NA

top_priority_rating_among_lt

Distribution

Distribution of values for top_priority_rating_among_lt

0 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	hist	label
top_priority_rating_among_lt	numeric	0	1	-Inf	4	5	-Inf	▁▁▃▇▆	NA

mn_priority_lt_rating

Distribution

Distribution of values for mn_priority_lt_rating

524 missing values.

Summary statistics

name	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist	label
mn_priority_lt_rating	numeric	524	0.76	1	3.4	5	3.3	0.71	▁▃▇▇▂	NA

start_date_qtl_by_referrer

Distribution

Distribution of values for start_date_qtl_by_referrer

0 missing values.

Summary statistics

name	data_type	ordered	value_labels	n_missing	complete_rate	n_unique	top_counts	label
start_date_qtl_by_referrer	factor	FALSE	[0%, 25%), 2. [25%, 50%], 3. (50%, 75%], 4. (75%, 100%]	0	1	4	[25: 802, (50: 588, (75: 426, [0%: 348	NA

Missingness report

description	income_c_imp	income_c_imp_k	ea_id2	first_hear_ea	engagement	engagement_num	engagement_f	d_engage_3_5	d_engage_4_5	d_engage_5	engage_cats_1	engage_cats_2	year_involved	action_chose_job_degree	action_applied_job_degree	action_donated	action_gwwc	action_organize_group	action_work_ea_org	action_change_major	action_wrote_thesis	action_internship	action_applied_ea_global	action_attended_ea_global	action_ea_forum	action_lead_group	action_applied_one_on_one	action_had_one_on_one	action_change_career	action_subscribe_80k	action_none	involve_80k	involve_givewell	involve_personal_contact	involve_book	involve_article_blog	involve_gwwc	involve_group	involve_online	involve_lesswrong	involve_slate_star	involve_podcast	involve_ea_global	involve_lycs	involve_ace	involve_eagx	involve_other	member_ea_fb	member_ea_forum	member_lesswrong	member_ea_group	member_none	influence_80k_one_on_one	influence_80k_website	influence_80k_podcast	influence_podcast_other	influence_personal_contact	influence_books	influence_gwwc	influence_local_group	influence_givewell	influence_ea_global	influence_eagx	influence_ace	influence_lycs	influence_ea_forum	influence_articles_blogs	influence_ea_survey	influence_facebook_groups	influence_lesswrong	influence_slate_star	influence_wanbam	influence_aac	influence_none	influence_other	status_employed_ft	status_employed_pt	status_self_employed	status_not_employed_looking	status_not_employed	status_homemaker_parent	status_retired	status_student_hs	status_student_undergrad	status_student_masters	status_student_doctoral	status_student_other	status_prefer_no_answer	status_	employ_status	d_student	career_still_deciding	career_building_capital	career_non_profit_ea	career_non_profit	career_for_profit_earn_to_give	career_for_profit	career_academia	career_government	career_think_tank_lobby	career_na	career_other	career_	lt_top_priority	first_generation_student	financial_instability	capital_over_impact	birth_year	age_approx	age_approx_ranges	age_approx_split	race_white	race_black_aa	race_hispanic_la_spanish	race_american_indian_alaskan	race_asian	race_native_hawaiin_pacific	race_prefer_no_answer	race_other	race_	race	lt_above_mn_priority	gender_original	gender_manual	d_male	prioritize_global_poverty	currency	prioritize_animal_welfare	prioritize_climate_change	city	friend_introduce	prioritize_biosecurity	agree_part_of_ea_community	prioritize_ai_risks	agree_ea_helps_impact	ea_community_ideal	ea_community_satisfaction	prioritize_ea_movement	prioritize_mental_health	donation_2019	prioritize_nuclear_security	income	income_k	donation_2020	prioritize_x_risks	sexual_orientation	prioritize_causes	donation_2019_c	don_19_p1	don_share_inc_19_imp	university_original	income_c	income_k_c	donation_2020_c	don_share_inc_19	prioritize_broad_longtermism	participate_contact	learned_80k	connection_80k	learned_ea_global	connection_ea_global	learned_ea_hub	connection_ea_hub	learned_ea_student_mentoring	connection_ea_student_mentor	learned_eagx	connection_eagx	learned_effective_thesis	connection_effective_thesis	learned_facebook_group	connection_facebook_group	learned_gwwc	connection_gwwc	learned_intl_ea_events	connection_intl_ea_events	learned_personal_connection	connection_personal_contact	learned_lesswrong	connection_lesswrong	learned_local_group	connection_local_groups	learned_non_local_group	connection_non_local_group	learned_ea_forum	connection_ea_forum	learned_ea_books	connection_ea_books	learned_ea_newsletter	connection_ea_newsletter	learned_none	connection_none	learned_connection_other	prioritize_lt	first_hear_ea_desc	negative_80k	negative_podcast	negative_givewell	negative_personal_contact	negative_books	negative_gwwc	negative_local_group	negative_lesswrong	negative_slate_star	negative_ea_global	negative_eagx	negative_facebook_group	negative_ea_forum	negative_articles_blogs	negative_ea_fellowship	negative_eagx2	negative_ea_newsletter	negative_wanbam	negative_none	negative_other	engaged_personal_contact	ea_community_why	prioritize_meta	agree_farmed_animals_concern	agree_ways_better_than_others	agree_longtermism	agree_quantify_compare_impact	agree_work_on_any_cause	reputation_effect	engaged_80k_hours	group_comfortable_friend	local_group_original	group_name_original	city_other	group_supports_action	engaged_80k_podcast	group_beliefs_humility	engaged_local_groups	engaged_online_community	engaged_givewell	engaged_ea_forum	engaged_ea_newsletter	engaged_slate_star	engaged_lesswrong	dislike_ea_community	bottleneck_productivity	reputation_effect_explanation	engaged_gwwc	participate_fellowship_causes	prioritize_other	substantial_affect_impact	participate_fellowship_adv	ea_org_or_project	participate_social_event	participate_fellowship_career	engaged_eagx	engaged_ea_global	negative_response	participate_the_precipice	participate_donation_discuss	dont_share_80k	participate_80k_pod_discuss	donate_other1	engaged_ea_fellowship	ea_id	participate_doing_good_better	ea_id3	participate_fellowship_intro	first_hear_ea_other	participate_gwwc_info_session	participate_intro_one_on_one	engaged_80k_one_on_one	engaged_wanbam	custom_data_1	var_miss	n_miss
Missing values per variable	40	40	175	254	259	259	259	259	259	259	259	259	270	280	280	280	280	280	280	280	280	280	280	280	280	280	280	280	280	280	280	290	290	290	290	290	290	290	290	290	290	290	290	290	290	290	290	310	310	310	310	310	413	413	413	413	413	413	413	413	413	413	413	413	413	413	413	413	413	413	413	413	413	413	413	472	472	472	472	472	472	472	472	472	472	472	472	472	472	472	472	487	487	487	487	487	487	487	487	487	487	487	487	491	492	493	496	505	505	505	505	507	507	507	507	507	507	507	507	507	507	524	526	536	536	539	555	561	561	562	581	583	584	601	603	617	624	639	641	647	652	665	665	669	678	686	689	697	697	708	712	713	713	718	723	758	765	829	829	829	829	829	829	829	829	829	829	829	829	829	829	829	829	829	829	829	829	829	829	829	829	829	829	829	829	829	829	829	829	829	829	829	908	968	1.03e+03	1.03e+03	1.03e+03	1.03e+03	1.03e+03	1.03e+03	1.03e+03	1.03e+03	1.03e+03	1.03e+03	1.03e+03	1.03e+03	1.03e+03	1.03e+03	1.03e+03	1.03e+03	1.03e+03	1.03e+03	1.03e+03	1.03e+03	1.07e+03	1.1e+03	1.11e+03	1.11e+03	1.12e+03	1.12e+03	1.12e+03	1.12e+03	1.17e+03	1.23e+03	1.29e+03	1.29e+03	1.29e+03	1.3e+03	1.3e+03	1.3e+03	1.3e+03	1.32e+03	1.36e+03	1.41e+03	1.44e+03	1.53e+03	1.59e+03	1.6e+03	1.61e+03	1.63e+03	1.67e+03	1.67e+03	1.69e+03	1.7e+03	1.7e+03	1.7e+03	1.72e+03	1.72e+03	1.74e+03	1.78e+03	1.79e+03	1.81e+03	1.85e+03	1.85e+03	1.89e+03	1.9e+03	1.91e+03	1.94e+03	1.94e+03	1.94e+03	1.95e+03	1.97e+03	2e+03	2.02e+03	2.03e+03	2.04e+03	2.06e+03	2.16e+03	2.06e+05	2.06e+05
Missing values in 265 variables	1	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	265	227
Missing values in 216 variables	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	216	34
Missing values in 215 variables	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	215	32
1817 other, less frequent patterns	1.78e+03	1.78e+03	1.66e+03	1.8e+03	1.8e+03	1.8e+03	1.8e+03	1.8e+03	1.8e+03	1.8e+03	1.8e+03	1.8e+03	1.79e+03	1.78e+03	1.78e+03	1.78e+03	1.78e+03	1.78e+03	1.78e+03	1.78e+03	1.78e+03	1.78e+03	1.78e+03	1.78e+03	1.78e+03	1.78e+03	1.78e+03	1.78e+03	1.78e+03	1.78e+03	1.78e+03	1.77e+03	1.77e+03	1.77e+03	1.77e+03	1.77e+03	1.77e+03	1.77e+03	1.77e+03	1.77e+03	1.77e+03	1.77e+03	1.77e+03	1.77e+03	1.77e+03	1.77e+03	1.77e+03	1.76e+03	1.76e+03	1.76e+03	1.76e+03	1.76e+03	1.75e+03	1.75e+03	1.75e+03	1.75e+03	1.75e+03	1.75e+03	1.75e+03	1.75e+03	1.75e+03	1.75e+03	1.75e+03	1.75e+03	1.75e+03	1.75e+03	1.75e+03	1.75e+03	1.75e+03	1.75e+03	1.75e+03	1.75e+03	1.75e+03	1.75e+03	1.75e+03	1.69e+03	1.69e+03	1.69e+03	1.69e+03	1.69e+03	1.69e+03	1.69e+03	1.69e+03	1.69e+03	1.69e+03	1.69e+03	1.69e+03	1.69e+03	1.69e+03	1.69e+03	1.69e+03	1.68e+03	1.68e+03	1.68e+03	1.68e+03	1.68e+03	1.68e+03	1.68e+03	1.68e+03	1.68e+03	1.68e+03	1.68e+03	1.68e+03	1.67e+03	1.67e+03	1.67e+03	1.67e+03	1.66e+03	1.66e+03	1.66e+03	1.66e+03	1.66e+03	1.66e+03	1.66e+03	1.66e+03	1.66e+03	1.66e+03	1.66e+03	1.66e+03	1.66e+03	1.66e+03	1.64e+03	1.64e+03	1.63e+03	1.63e+03	1.62e+03	1.61e+03	1.6e+03	1.6e+03	1.6e+03	1.58e+03	1.58e+03	1.58e+03	1.56e+03	1.56e+03	1.55e+03	1.54e+03	1.52e+03	1.52e+03	1.52e+03	1.51e+03	1.5e+03	1.5e+03	1.5e+03	1.49e+03	1.48e+03	1.48e+03	1.47e+03	1.47e+03	1.46e+03	1.45e+03	1.45e+03	1.45e+03	1.45e+03	1.44e+03	1.41e+03	1.4e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.34e+03	1.26e+03	1.14e+03	1.14e+03	1.14e+03	1.14e+03	1.14e+03	1.14e+03	1.14e+03	1.14e+03	1.14e+03	1.14e+03	1.14e+03	1.14e+03	1.14e+03	1.14e+03	1.14e+03	1.14e+03	1.14e+03	1.14e+03	1.14e+03	1.14e+03	1.14e+03	1.1e+03	1.06e+03	1.06e+03	1.05e+03	1.05e+03	1.05e+03	1.04e+03	1.04e+03	995	930	861	857	857	868	854	866	851	844	802	754	721	636	575	563	553	537	496	491	470	467	465	462	441	443	429	389	374	355	317	310	271	263	252	227	221	223	210	191	160	145	134	119	109	0	1.2e+05	1.87e+03

Codebook table

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{
  "name": ".",
  "datePublished": "2021-03-03",
  "description": "The dataset has N=2164 rows and 310 columns.\n0 rows have no missing values on any column.\n\n\n## Table of variables\nThis table contains variable names, labels, and number of missing values.\nSee the complete codebook for more.\n\n[truncated]\n\n### Note\nThis dataset was automatically described using the [codebook R package](https://rubenarslan.github.io/codebook/) (version 0.9.2).",
  "keywords": ["respondentid", "collectorid", "start_date", "end_date", "custom_data_1", "opt_out_cea", "first_hear_ea_other", "first_hear_ea_desc", "involve_80k", "involve_givewell", "involve_personal_contact", "involve_book", "involve_article_blog", "involve_gwwc", "involve_group", "involve_online", "involve_lesswrong", "involve_slate_star", "involve_podcast", "involve_ea_global", "involve_lycs", "involve_ace", "involve_eagx", "involve_other", "action_chose_job_degree", "action_applied_job_degree", "action_donated", "action_gwwc", "action_organize_group", "action_work_ea_org", "action_change_major", "action_wrote_thesis", "action_internship", "action_applied_ea_global", "action_attended_ea_global", "action_ea_forum", "action_lead_group", "action_applied_one_on_one", "action_had_one_on_one", "action_change_career", "action_subscribe_80k", "action_none", "ea_org_or_project", "member_ea_fb", "member_ea_forum", "member_lesswrong", "member_ea_group", "member_none", "local_group_original", "group_comfortable_friend", "group_beliefs_humility", "group_supports_action", "influence_80k_one_on_one", "influence_80k_website", "influence_80k_podcast", "influence_podcast_other", "influence_personal_contact", "influence_books", "influence_gwwc", "influence_local_group", "influence_givewell", "influence_ea_global", "influence_eagx", "influence_ace", "influence_lycs", "influence_ea_forum", "influence_articles_blogs", "influence_ea_survey", "influence_facebook_groups", "influence_lesswrong", "influence_slate_star", "influence_wanbam", "influence_aac", "influence_none", "influence_other", "negative_80k", "negative_podcast", "negative_givewell", "negative_personal_contact", "negative_books", "negative_gwwc", "negative_local_group", "negative_lesswrong", "negative_slate_star", "negative_ea_global", "negative_eagx", "negative_facebook_group", "negative_ea_forum", "negative_articles_blogs", "negative_ea_fellowship", "negative_eagx2", "negative_ea_newsletter", "negative_wanbam", "negative_none", "negative_other", "negative_response", "engaged_ea_forum", "engaged_online_community", "engaged_local_groups", "engaged_ea_fellowship", "engaged_gwwc", "engaged_ea_global", "engaged_eagx", "engaged_ea_newsletter", "engaged_wanbam", "engaged_personal_contact", "engaged_80k_podcast", "engaged_80k_hours", "engaged_80k_one_on_one", "engaged_givewell", "engaged_lesswrong", "engaged_slate_star", "substantial_affect_impact", "prioritize_animal_welfare", "prioritize_causes", "prioritize_climate_change", "prioritize_biosecurity", "prioritize_nuclear_security", "prioritize_ai_risks", "prioritize_mental_health", "prioritize_global_poverty", "prioritize_meta", "prioritize_ea_movement", "prioritize_x_risks", "prioritize_broad_longtermism", "prioritize_other", "currency", "currency_other", "income", "donation_2019", "donation_2020", "donate_later", "university_original", "birth_year", "gender_original", "sexual_orientation", "country", "city_other", "ea_community_ideal", "ea_community_satisfaction", "ea_community_why", "agree_ea_helps_impact", "agree_part_of_ea_community", "friend_introduce", "learned_80k", "connection_80k", "learned_ea_global", "connection_ea_global", "learned_ea_hub", "connection_ea_hub", "learned_ea_student_mentoring", "connection_ea_student_mentor", "learned_eagx", "connection_eagx", "learned_effective_thesis", "connection_effective_thesis", "learned_facebook_group", "connection_facebook_group", "learned_gwwc", "connection_gwwc", "learned_intl_ea_events", "connection_intl_ea_events", "learned_personal_connection", "connection_personal_contact", "learned_lesswrong", "connection_lesswrong", "learned_local_group", "connection_local_groups", "learned_non_local_group", "connection_non_local_group", "learned_ea_forum", "connection_ea_forum", "learned_ea_books", "connection_ea_books", "learned_ea_newsletter", "connection_ea_newsletter", "learned_none", "connection_none", "learned_connection_other", "participate_doing_good_better", "participate_the_precipice", "participate_fellowship_intro", "participate_fellowship_adv", "participate_80k_pod_discuss", "participate_fellowship_career", "participate_fellowship_causes", "participate_intro_one_on_one", "participate_gwwc_info_session", "participate_donation_discuss", "participate_social_event", "participate_contact", "email_next_survey", "email_followup_surveys", "email_dont_email", "share_80k", "dont_share_80k", "profile_ea_hub", "agree_quantify_compare_impact", "agree_ways_better_than_others", "agree_work_on_any_cause", "agree_farmed_animals_concern", "agree_longtermism", "reputation_effect_explanation", "bottleneck_productivity", "dislike_ea_community", "donate_rethink_charity", "donate_80k", "donate_center_applied_rational", "donate_mercy_for_animals", "donate_other1", "donate_other2", "donate_other3", "donate_other4", "donate_other5", "datecreated", "group_name_original", "group_name_manual", "first_hear_qual", "_merge", "ea_id", "ea_id2", "ea_id3", "engagement", "capital_over_impact", "financial_instability", "first_generation_student", "reputation_effect", "year_involved", "first_hear_ea", "city", "collector_source", "gender_manual", "race_white", "race_black_aa", "race_hispanic_la_spanish", "race_american_indian_alaskan", "race_asian", "race_native_hawaiin_pacific", "race_prefer_no_answer", "race_other", "race_", "status_employed_ft", "status_employed_pt", "status_self_employed", "status_not_employed_looking", "status_not_employed", "status_homemaker_parent", "status_retired", "status_student_hs", "status_student_undergrad", "status_student_masters", "status_student_doctoral", "status_student_other", "status_prefer_no_answer", "status_", "career_still_deciding", "career_building_capital", "career_non_profit_ea", "career_non_profit", "career_for_profit_earn_to_give", "career_for_profit", "career_academia", "career_government", "career_think_tank_lobby", "career_na", "career_other", "career_", "race", "age_approx", "employ_status", "age_approx_ranges", "age_approx_split", "engagement_num", "engagement_f", "d_engage_3_5", "d_engage_4_5", "d_engage_5", "income_k", "d_male", "d_student", "d_live_usa", "prioritize_lt", "referrer", "referrer_cat", "referrer_min100", "referrer_cat2", "referrer_cat3", "engage_cats_1", "engage_cats_2", "start_date_quantiles", "start_date_thirds_by_referrer", "survey_willing", "donation_2019_c", "donation_2020_c", "income_c", "income_k_c", "income_c_imp", "don_share_inc_19", "don_share_inc_19_imp", "don_19_p1", "income_c_imp_k", "action_gwwc_f", "top_priority_rating", "avg_priority_rating", "mn_priority_rating", "lt_top_priority", "lt_above_mn_priority", "top_priority_rating_among_lt", "mn_priority_lt_rating", "start_date_qtl_by_referrer"],
  "@context": "http://schema.org/",
  "@type": "Dataset",
  "variableMeasured": [
    {
      "name": "respondentid",
      "description": "Respondent ID ",
      "@type": "propertyValue"
    },
    {
      "name": "collectorid",
      "description": "Collector ID ",
      "@type": "propertyValue"
    },
    {
      "name": "start_date",
      "description": "Start Date ",
      "@type": "propertyValue"
    },
    {
      "name": "end_date",
      "description": "End Date ",
      "@type": "propertyValue"
    },
    {
      "name": "custom_data_1",
      "description": "Custom Data 1 ",
      "@type": "propertyValue"
    },
    {
      "name": "opt_out_cea",
      "description": "Opt out of data sharing with the Centre for Effective Altruism ",
      "@type": "propertyValue"
    },
    {
      "name": "first_hear_ea_other",
      "description": "How did you first hear about effective altruism? Other",
      "@type": "propertyValue"
    },
    {
      "name": "first_hear_ea_desc",
      "description": "Please briefly specify any further details about how you first heard about EA. ",
      "@type": "propertyValue"
    },
    {
      "name": "involve_80k",
      "description": "Important for you getting involved in EA? 80,000 Hours",
      "@type": "propertyValue"
    },
    {
      "name": "involve_givewell",
      "description": "Important for you getting involved in EA? GiveWell",
      "@type": "propertyValue"
    },
    {
      "name": "involve_personal_contact",
      "description": "Important for you getting involved in EA? Personal contact with EAs",
      "@type": "propertyValue"
    },
    {
      "name": "involve_book",
      "description": "Important for you getting involved in EA? A book",
      "@type": "propertyValue"
    },
    {
      "name": "involve_article_blog",
      "description": "Important for you getting involved in EA? An article or blog",
      "@type": "propertyValue"
    },
    {
      "name": "involve_gwwc",
      "description": "Important for you getting involved in EA? Giving What We Can",
      "@type": "propertyValue"
    },
    {
      "name": "involve_group",
      "description": "Important for you getting involved in EA? Local or university EA Group",
      "@type": "propertyValue"
    },
    {
      "name": "involve_online",
      "description": "Important for you getting involved in EA? The online EA community",
      "@type": "propertyValue"
    },
    {
      "name": "involve_lesswrong",
      "description": "Important for you getting involved in EA? LessWrong",
      "@type": "propertyValue"
    },
    {
      "name": "involve_slate_star",
      "description": "Important for you getting involved in EA? Slate Star Codex",
      "@type": "propertyValue"
    },
    {
      "name": "involve_podcast",
      "description": "Important for you getting involved in EA? Podcast",
      "@type": "propertyValue"
    },
    {
      "name": "involve_ea_global",
      "description": "Important for you getting involved in EA? EA Global",
      "@type": "propertyValue"
    },
    {
      "name": "involve_lycs",
      "description": "Important for you getting involved in EA? The Life You Can Save",
      "@type": "propertyValue"
    },
    {
      "name": "involve_ace",
      "description": "Important for you getting involved in EA? Animal Charity Evaluators",
      "@type": "propertyValue"
    },
    {
      "name": "involve_eagx",
      "description": "Important for you getting involved in EA? EAGx",
      "@type": "propertyValue"
    },
    {
      "name": "involve_other",
      "description": "Important for you getting involved in EA? Other (please specify)",
      "@type": "propertyValue"
    },
    {
      "name": "action_chose_job_degree",
      "description": "Action: Chose a job or graduate degree program based on EA principles",
      "@type": "propertyValue"
    },
    {
      "name": "action_applied_job_degree",
      "description": "Action: Applied for a job or graduate degree program based on EA principles",
      "@type": "propertyValue"
    },
    {
      "name": "action_donated",
      "description": "Action: Donated >10% of your income based on EA principles",
      "@type": "propertyValue"
    },
    {
      "name": "action_gwwc",
      "description": "Action: Took the Giving What We Can pledge",
      "@type": "propertyValue"
    },
    {
      "name": "action_organize_group",
      "description": "Action: Spent >6 hours/week for >=2 months organizing an EA group/project",
      "@type": "propertyValue"
    },
    {
      "name": "action_work_ea_org",
      "description": "Action: Worked (or currently work) at an EA organization",
      "@type": "propertyValue"
    },
    {
      "name": "action_change_major",
      "description": "Action: Changed your major in university based on EA principles",
      "@type": "propertyValue"
    },
    {
      "name": "action_wrote_thesis",
      "description": "Action: Wrote a thesis based on EA principles",
      "@type": "propertyValue"
    },
    {
      "name": "action_internship",
      "description": "Action: Internship related to a career path you are exploring based on EA",
      "@type": "propertyValue"
    },
    {
      "name": "action_applied_ea_global",
      "description": "Action: Applied to EA Global",
      "@type": "propertyValue"
    },
    {
      "name": "action_attended_ea_global",
      "description": "Action: Attended EA Global",
      "@type": "propertyValue"
    },
    {
      "name": "action_ea_forum",
      "description": "Action: Posted or commented on the EA Forum",
      "@type": "propertyValue"
    },
    {
      "name": "action_lead_group",
      "description": "Action: Been a leader of a local EA group",
      "@type": "propertyValue"
    },
    {
      "name": "action_applied_one_on_one",
      "description": "Action: Applied for a one-on-one career discussion with 80,000 Hours",
      "@type": "propertyValue"
    },
    {
      "name": "action_had_one_on_one",
      "description": "Action: Had a one-on-one career discussion with 80,000 Hours",
      "@type": "propertyValue"
    },
    {
      "name": "action_change_career",
      "description": "Action: Changed your career plans based on EA principles",
      "@type": "propertyValue"
    },
    {
      "name": "action_subscribe_80k",
      "description": "Action: Subscribed to the 80,000 Hours newsletter",
      "@type": "propertyValue"
    },
    {
      "name": "action_none",
      "description": "Action: None of the above",
      "@type": "propertyValue"
    },
    {
      "name": "ea_org_or_project",
      "description": "Name of EA org/project you worked on or interned for. ",
      "@type": "propertyValue"
    },
    {
      "name": "member_ea_fb",
      "description": "Which of the following are you a member of? EA Facebook group",
      "@type": "propertyValue"
    },
    {
      "name": "member_ea_forum",
      "description": "Which of the following are you a member of? The Effective Altruism Forum",
      "@type": "propertyValue"
    },
    {
      "name": "member_lesswrong",
      "description": "Which of the following are you a member of? LessWrong",
      "@type": "propertyValue"
    },
    {
      "name": "member_ea_group",
      "description": "Which of the following are you a member of? Local EA group",
      "@type": "propertyValue"
    },
    {
      "name": "member_none",
      "description": "Which of the following are you a member of? None of the above",
      "@type": "propertyValue"
    },
    {
      "name": "local_group_original",
      "description": "If you are a member of a local EA group, which group are you a member of? ",
      "@type": "propertyValue"
    },
    {
      "name": "group_comfortable_friend",
      "description": " My group is a place to which I'd feel comfortable bringing a friend",
      "value": "1. (1) Strongly disagree,\n2. (2) Disagree,\n3. (3) Neither agree nor disagree,\n4. (4) Agree,\n5. (5) Strongly agree",
      "@type": "propertyValue"
    },
    {
      "name": "group_beliefs_humility",
      "description": " My group is a place where people express their beliefs with humility",
      "value": "1. (1) Strongly disagree,\n2. (2) Disagree,\n3. (3) Neither agree nor disagree,\n4. (4) Agree,\n5. (5) Strongly agree",
      "@type": "propertyValue"
    },
    {
      "name": "group_supports_action",
      "description": " My group supports me in taking action based on EA principles",
      "value": "1. (1) Strongly disagree,\n2. (2) Disagree,\n3. (3) Neither agree nor disagree,\n4. (4) Agree,\n5. (5) Strongly agree",
      "@type": "propertyValue"
    },
    {
      "name": "influence_80k_one_on_one",
      "description": "Influence your ability to make impact? 80,000 Hours (1-on-1 career discussion)",
      "@type": "propertyValue"
    },
    {
      "name": "influence_80k_website",
      "description": "Influence your ability to make impact? 80,000 Hours (website)",
      "@type": "propertyValue"
    },
    {
      "name": "influence_80k_podcast",
      "description": "Influence your ability to make impact? 80,000 Hours (podcast)",
      "@type": "propertyValue"
    },
    {
      "name": "influence_podcast_other",
      "description": "Influence your ability to make impact? Podcast (other than 80,000 Hours)",
      "@type": "propertyValue"
    },
    {
      "name": "influence_personal_contact",
      "description": "Influence your ability to make impact? Personal contact with EAs",
      "@type": "propertyValue"
    },
    {
      "name": "influence_books",
      "description": "Influence your ability to make impact? Books related to EA",
      "@type": "propertyValue"
    },
    {
      "name": "influence_gwwc",
      "description": "Influence your ability to make impact? Giving What We Can",
      "@type": "propertyValue"
    },
    {
      "name": "influence_local_group",
      "description": "Influence your ability to make impact? Local EA groups",
      "@type": "propertyValue"
    },
    {
      "name": "influence_givewell",
      "description": "Influence your ability to make impact? GiveWell",
      "@type": "propertyValue"
    },
    {
      "name": "influence_ea_global",
      "description": "Influence your ability to make impact? EA Global",
      "@type": "propertyValue"
    },
    {
      "name": "influence_eagx",
      "description": "Influence your ability to make impact? EAGx",
      "@type": "propertyValue"
    },
    {
      "name": "influence_ace",
      "description": "Influence your ability to make impact? Animal Charity Evaluators",
      "@type": "propertyValue"
    },
    {
      "name": "influence_lycs",
      "description": "Influence your ability to make impact? The Life You Can Save",
      "@type": "propertyValue"
    },
    {
      "name": "influence_ea_forum",
      "description": "Influence your ability to make impact? The EA Forum",
      "@type": "propertyValue"
    },
    {
      "name": "influence_articles_blogs",
      "description": "Influence your ability to make impact? Articles/blogs related to EA",
      "@type": "propertyValue"
    },
    {
      "name": "influence_ea_survey",
      "description": "Influence your ability to make impact? The EA Newsletter",
      "@type": "propertyValue"
    },
    {
      "name": "influence_facebook_groups",
      "description": "Influence your ability to make impact? Facebook groups related to EA",
      "@type": "propertyValue"
    },
    {
      "name": "influence_lesswrong",
      "description": "Influence your ability to make impact? LessWrong",
      "@type": "propertyValue"
    },
    {
      "name": "influence_slate_star",
      "description": "Influence your ability to make impact? Slate Star Codex",
      "@type": "propertyValue"
    },
    {
      "name": "influence_wanbam",
      "description": "Influence your ability to make impact? WANBAM",
      "@type": "propertyValue"
    },
    {
      "name": "influence_aac",
      "description": "Influence your ability to make impact? Animal Advocacy Careers",
      "@type": "propertyValue"
    },
    {
      "name": "influence_none",
      "description": "Influence your ability to make impact? None of the above",
      "@type": "propertyValue"
    },
    {
      "name": "influence_other",
      "description": "Influence your ability to make impact? Other",
      "@type": "propertyValue"
    },
    {
      "name": "negative_80k",
      "description": "Negative impact on your involvement with EA so far? 80,000 Hours",
      "@type": "propertyValue"
    },
    {
      "name": "negative_podcast",
      "description": "Negative impact on your involvement with EA so far? Podcast (not 80,000 Hours)",
      "@type": "propertyValue"
    },
    {
      "name": "negative_givewell",
      "description": "Negative impact on your involvement with EA so far? GiveWell",
      "@type": "propertyValue"
    },
    {
      "name": "negative_personal_contact",
      "description": "Negative impact on your involvement with EA so far? Personal contact with EAs",
      "@type": "propertyValue"
    },
    {
      "name": "negative_books",
      "description": "Negative impact on your involvement with EA so far? Books related to EA",
      "@type": "propertyValue"
    },
    {
      "name": "negative_gwwc",
      "description": "Negative impact on your involvement with EA so far? Giving What We Can",
      "@type": "propertyValue"
    },
    {
      "name": "negative_local_group",
      "description": "Negative impact on your involvement with EA so far? Local EA groups",
      "@type": "propertyValue"
    },
    {
      "name": "negative_lesswrong",
      "description": "Negative impact on your involvement with EA so far? LessWrong",
      "@type": "propertyValue"
    },
    {
      "name": "negative_slate_star",
      "description": "Negative impact on your involvement with EA so far? SlateStarCodex",
      "@type": "propertyValue"
    },
    {
      "name": "negative_ea_global",
      "description": "Negative impact on your involvement with EA so far? EA Global",
      "@type": "propertyValue"
    },
    {
      "name": "negative_eagx",
      "description": "Negative impact on your involvement with EA so far? EAGx",
      "@type": "propertyValue"
    },
    {
      "name": "negative_facebook_group",
      "description": "Negative impact on your involvement with EA so far? FB groups related to EA",
      "@type": "propertyValue"
    },
    {
      "name": "negative_ea_forum",
      "description": "Negative impact on your involvement with EA so far? The EA Forum",
      "@type": "propertyValue"
    },
    {
      "name": "negative_articles_blogs",
      "description": "Negative impact on your involvement with EA so far? Articles/blogs related EA",
      "@type": "propertyValue"
    },
    {
      "name": "negative_ea_fellowship",
      "description": "Negative impact on your involvement with EA so far? An EA Fellowship",
      "@type": "propertyValue"
    },
    {
      "name": "negative_eagx2",
      "description": "Negative impact on your involvement with EA so far? EAGx",
      "@type": "propertyValue"
    },
    {
      "name": "negative_ea_newsletter",
      "description": "Negative impact on your involvement with EA so far? The EA Newsletter",
      "@type": "propertyValue"
    },
    {
      "name": "negative_wanbam",
      "description": "Negative impact on your involvement with EA so far? WANBAM",
      "@type": "propertyValue"
    },
    {
      "name": "negative_none",
      "description": "Negative impact on your involvement with EA so far? None of the above",
      "@type": "propertyValue"
    },
    {
      "name": "negative_other",
      "description": "Negative impact on your involvement with EA so far? Other",
      "@type": "propertyValue"
    },
    {
      "name": "negative_response",
      "description": "Negative impact on your involvement with EA so far? Open-Ended Response",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_ea_forum",
      "description": "Affected your likelihood of staying engaged with EA? The EA Forum",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_online_community",
      "description": "Affected your likelihood of staying engaged with EA? The online EA community",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_local_groups",
      "description": "Affected your likelihood of staying engaged with EA? Local EA groups",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_ea_fellowship",
      "description": "Affected your likelihood of staying engaged with EA? An EA Fellowship",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_gwwc",
      "description": "Affected your likelihood of staying engaged with EA? Giving What We Can",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_ea_global",
      "description": "Affected your likelihood of staying engaged with EA? EA Global",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_eagx",
      "description": "Affected your likelihood of staying engaged with EA? EAGx",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_ea_newsletter",
      "description": "Affected your likelihood of staying engaged with EA? The EA Newsletter",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_wanbam",
      "description": "Affected your likelihood of staying engaged with EA? WANBAM",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_personal_contact",
      "description": "Affected your likelihood of staying engaged with EA? Personal contacts",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_80k_podcast",
      "description": "Affected your likelihood of staying engaged with EA? 80,000 Hours (podcast)",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_80k_hours",
      "description": "Affected your likelihood of staying engaged with EA? 80,000 Hours (website)",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_80k_one_on_one",
      "description": "Affected your likelihood of staying engaged with EA? 80k Hours (1-on-1 career)",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_givewell",
      "description": "Affected your likelihood of staying engaged with EA? GiveWell",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_lesswrong",
      "description": "Affected your likelihood of staying engaged with EA? LessWrong",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_slate_star",
      "description": "Affected your likelihood of staying engaged with EA? Slate Star Codex",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "substantial_affect_impact",
      "description": "Are there other things which have substantially affected your impact? ",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_animal_welfare",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_causes",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_climate_change",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_biosecurity",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_nuclear_security",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_ai_risks",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_mental_health",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_global_poverty",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_meta",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_ea_movement",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_x_risks",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_broad_longtermism",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_other",
      "description": "Are there any other causes you feel should be priorities for the EA community? ",
      "@type": "propertyValue"
    },
    {
      "name": "currency",
      "@type": "propertyValue"
    },
    {
      "name": "currency_other",
      "description": "Please select the currency that pertains to you. Other",
      "@type": "propertyValue"
    },
    {
      "name": "income",
      "description": "What was your pre-tax individual income in 2019? ",
      "@type": "propertyValue"
    },
    {
      "name": "donation_2019",
      "description": "In 2019, roughly how much money did you donate? ",
      "@type": "propertyValue"
    },
    {
      "name": "donation_2020",
      "description": "In 2020, how much do you currently plan to donate? ",
      "@type": "propertyValue"
    },
    {
      "name": "donate_later",
      "description": "Are you presently saving money to donate later, rather than donate now? ",
      "@type": "propertyValue"
    },
    {
      "name": "university_original",
      "description": "If applicable, which university or universities did you attend? ",
      "@type": "propertyValue"
    },
    {
      "name": "birth_year",
      "description": "In which year were you born? ",
      "@type": "propertyValue"
    },
    {
      "name": "gender_original",
      "description": "Gender, original ",
      "@type": "propertyValue"
    },
    {
      "name": "sexual_orientation",
      "description": "What is your sexual orientation? ",
      "@type": "propertyValue"
    },
    {
      "name": "country",
      "@type": "propertyValue"
    },
    {
      "name": "city_other",
      "description": "In what town/city/metropolitan area do you live? Other",
      "@type": "propertyValue"
    },
    {
      "name": "ea_community_ideal",
      "description": "How well does the EA community compare to your ideal? ",
      "@type": "propertyValue"
    },
    {
      "name": "ea_community_satisfaction",
      "description": "What is your overall satisfaction with the EA community? ",
      "@type": "propertyValue"
    },
    {
      "name": "ea_community_why",
      "description": "Why did you give the two ratings above? Open-Ended Response",
      "@type": "propertyValue"
    },
    {
      "name": "agree_ea_helps_impact",
      "description": "Agree: The EA community helps me have more impact.",
      "value": "1. (1) Strongly disagree,\n2. (2) Disagree,\n3. (3) Neither agree nor disagree,\n4. (4) Agree,\n5. (5) Strongly agree",
      "@type": "propertyValue"
    },
    {
      "name": "agree_part_of_ea_community",
      "description": "Agree: I feel that I am a part of the effective altruism community.",
      "value": "1. (1) Strongly disagree,\n2. (2) Disagree,\n3. (3) Neither agree nor disagree,\n4. (4) Agree,\n5. (5) Strongly agree",
      "@type": "propertyValue"
    },
    {
      "name": "friend_introduce",
      "description": "How excited would you be to introduce a friend to the EA community? ",
      "@type": "propertyValue"
    },
    {
      "name": "learned_80k",
      "description": " 80,000 Hours - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_80k",
      "description": " 80,000 Hours - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_ea_global",
      "description": " EA Global - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_ea_global",
      "description": " EA Global - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_ea_hub",
      "description": " EA Hub - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_ea_hub",
      "description": " EA Hub - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_ea_student_mentoring",
      "description": " EA Student Career Mentoring - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_ea_student_mentor",
      "description": " EA Student Career Mentoring - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_eagx",
      "description": " EAGx - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_eagx",
      "description": " EAGx - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_effective_thesis",
      "description": " Effective Thesis - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_effective_thesis",
      "description": " Effective Thesis - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_facebook_group",
      "description": " Facebook groups related to EA - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_facebook_group",
      "description": " Facebook groups related to EA - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_gwwc",
      "description": " Giving What We Can - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_gwwc",
      "description": " Giving What We Can - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_intl_ea_events",
      "description": " International EA social events - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_intl_ea_events",
      "description": " International EA social events - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_personal_connection",
      "description": " A personal connection - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_personal_contact",
      "description": " A personal connection - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_lesswrong",
      "description": " LessWrong - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_lesswrong",
      "description": " LessWrong - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_local_group",
      "description": " Local EA groups - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_local_groups",
      "description": " Local EA groups - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_non_local_group",
      "description": " Non-local meetups - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_non_local_group",
      "description": " Non-local meetups - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_ea_forum",
      "description": " The EA Forum - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_ea_forum",
      "description": " The EA Forum - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_ea_books",
      "description": " EA books - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_ea_books",
      "description": " EA books - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_ea_newsletter",
      "description": " The EA Newsletter - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_ea_newsletter",
      "description": " The EA Newsletter - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_none",
      "description": " None of the above - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_none",
      "description": " None of the above - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_connection_other",
      "description": " Other (please specify)",
      "@type": "propertyValue"
    },
    {
      "name": "participate_doing_good_better",
      "description": "Interested in: A reading group to discuss Doing Good Better",
      "@type": "propertyValue"
    },
    {
      "name": "participate_the_precipice",
      "description": "Interested in: A reading group to discuss The Precipice",
      "@type": "propertyValue"
    },
    {
      "name": "participate_fellowship_intro",
      "description": "Interested in: A fellowship covering the basics of effective altruism",
      "@type": "propertyValue"
    },
    {
      "name": "participate_fellowship_adv",
      "description": "Interested in: A fellowship covering advanced principles of effective altruism",
      "@type": "propertyValue"
    },
    {
      "name": "participate_80k_pod_discuss",
      "description": "Interested in: An 80,000 Hours podcast discussion group",
      "@type": "propertyValue"
    },
    {
      "name": "participate_fellowship_career",
      "description": "Interested in: A 4-part fellowship using the 80k tool for career planning",
      "@type": "propertyValue"
    },
    {
      "name": "participate_fellowship_causes",
      "description": "Interested in: A  fellowship covering key ideas related to your top cause area",
      "@type": "propertyValue"
    },
    {
      "name": "participate_intro_one_on_one",
      "description": "Interested in: An introductory 1-on-1 convo to discuss the basic ideas of EA",
      "@type": "propertyValue"
    },
    {
      "name": "participate_gwwc_info_session",
      "description": "Interested in: A one-time information session about GWWC / Try Giving",
      "@type": "propertyValue"
    },
    {
      "name": "participate_donation_discuss",
      "description": "Interested in: A one-time discussion about where other EAs are donating",
      "@type": "propertyValue"
    },
    {
      "name": "participate_social_event",
      "description": "Interested in: A one-time (virtual) social event to meet local EAs",
      "@type": "propertyValue"
    },
    {
      "name": "participate_contact",
      "description": "May we (CEA) contact you if the activit(ies) you selected become(s) available? ",
      "@type": "propertyValue"
    },
    {
      "name": "email_next_survey",
      "description": " Please send me an e-mail to next year's survey",
      "@type": "propertyValue"
    },
    {
      "name": "email_followup_surveys",
      "description": " Please e-mail me relevant followup surveys",
      "@type": "propertyValue"
    },
    {
      "name": "email_dont_email",
      "description": " Don't e-mail me about future surveys",
      "@type": "propertyValue"
    },
    {
      "name": "share_80k",
      "description": " Yes - I give my permission for this information to be shared with 80,000 Hours",
      "@type": "propertyValue"
    },
    {
      "name": "dont_share_80k",
      "description": " No - I do not wish for any of my information to be shared with 80,000 Hours",
      "@type": "propertyValue"
    },
    {
      "name": "profile_ea_hub",
      "description": "Would you like a personal profile on the EA Hub? ",
      "@type": "propertyValue"
    },
    {
      "name": "agree_quantify_compare_impact",
      "description": "Agree: It's possible to roughly quantify and compare different types of impact",
      "value": "1. (1) Strongly disagree,\n2. (2) Disagree,\n3. (3) Slightly disagree,\n4. (4) Neither agree nor disagree,\n5. (5) Slightly agree,\n6. (6) Agree,\n7. (7) Strongly agree",
      "@type": "propertyValue"
    },
    {
      "name": "agree_ways_better_than_others",
      "description": "Agree: Some ways of doing good are substantially better than others",
      "value": "1. (1) Strongly disagree,\n2. (2) Disagree,\n3. (3) Slightly disagree,\n4. (4) Neither agree nor disagree,\n5. (5) Slightly agree,\n6. (6) Agree,\n7. (7) Strongly agree",
      "@type": "propertyValue"
    },
    {
      "name": "agree_work_on_any_cause",
      "description": "Agree: It makes sense to be open to working on any cause",
      "value": "1. (1) Strongly disagree,\n2. (2) Disagree,\n3. (3) Slightly disagree,\n4. (4) Neither agree nor disagree,\n5. (5) Slightly agree,\n6. (6) Agree,\n7. (7) Strongly agree",
      "@type": "propertyValue"
    },
    {
      "name": "agree_farmed_animals_concern",
      "description": "Agree: Farmed animals deserve our moral concern",
      "value": "1. (1) Strongly disagree,\n2. (2) Disagree,\n3. (3) Slightly disagree,\n4. (4) Neither agree nor disagree,\n5. (5) Slightly agree,\n6. (6) Agree,\n7. (7) Strongly agree",
      "@type": "propertyValue"
    },
    {
      "name": "agree_longtermism",
      "description": "Agree: The impact of our actions on the very long-term future is most important",
      "value": "1. (1) Strongly disagree,\n2. (2) Disagree,\n3. (3) Slightly disagree,\n4. (4) Neither agree nor disagree,\n5. (5) Slightly agree,\n6. (6) Agree,\n7. (7) Strongly agree",
      "@type": "propertyValue"
    },
    {
      "name": "reputation_effect_explanation",
      "description": "If possible, could you please explain your answer? ",
      "@type": "propertyValue"
    },
    {
      "name": "bottleneck_productivity",
      "description": "Are there any things which you think currently bottleneck your positive impact? ",
      "@type": "propertyValue"
    },
    {
      "name": "dislike_ea_community",
      "description": "What do you personally dislike about the EA community and EA/EA-adjacent ideas? ",
      "@type": "propertyValue"
    },
    {
      "name": "donate_rethink_charity",
      "description": "Roughly how much did you donate in 2019? Rethink Charity",
      "@type": "propertyValue"
    },
    {
      "name": "donate_80k",
      "description": "Roughly how much did you donate in 2019? 80,000 Hours",
      "@type": "propertyValue"
    },
    {
      "name": "donate_center_applied_rational",
      "description": "Roughly how much did you donate in 2019? Center For Applied Rationality",
      "@type": "propertyValue"
    },
    {
      "name": "donate_mercy_for_animals",
      "description": "Roughly how much did you donate in 2019? Mercy For Animals",
      "@type": "propertyValue"
    },
    {
      "name": "donate_other1",
      "description": "Roughly how much did you donate in 2019? Other (please specify)",
      "@type": "propertyValue"
    },
    {
      "name": "donate_other2",
      "description": "Roughly how much did you donate in 2019? Other 2 (please specify)",
      "@type": "propertyValue"
    },
    {
      "name": "donate_other3",
      "description": "Roughly how much did you donate in 2019? Other 3 (please specify)",
      "@type": "propertyValue"
    },
    {
      "name": "donate_other4",
      "description": "Roughly how much did you donate in 2019? Other 4 (please specify)",
      "@type": "propertyValue"
    },
    {
      "name": "donate_other5",
      "description": "Roughly how much did you donate in 2019? Other 5 (please specify)",
      "@type": "propertyValue"
    },
    {
      "name": "datecreated",
      "description": "Date Created",
      "@type": "propertyValue"
    },
    {
      "name": "group_name_original",
      "description": "",
      "@type": "propertyValue"
    },
    {
      "name": "group_name_manual",
      "description": "Group Name, manually assigned",
      "@type": "propertyValue"
    },
    {
      "name": "first_hear_qual",
      "description": "",
      "@type": "propertyValue"
    },
    {
      "name": "_merge",
      "description": "",
      "value": "1. master only (1),\n2. using only (2),\n3. matched (3),\n4. missing updated (4),\n5. nonmissing conflict (5)",
      "@type": "propertyValue"
    },
    {
      "name": "ea_id",
      "@type": "propertyValue"
    },
    {
      "name": "ea_id2",
      "@type": "propertyValue"
    },
    {
      "name": "ea_id3",
      "@type": "propertyValue"
    },
    {
      "name": "engagement",
      "value": "1. (1) No engagement,\n2. (2) Mild engagement,\n3. (3) Moderate engagement,\n4. (4) Considerable engagement,\n5. (5) High engagement",
      "@type": "propertyValue"
    },
    {
      "name": "capital_over_impact",
      "value": "1. Modestly prioritizing career capital,\n2. Modestly prioritizing immediate impact,\n3. N/A,\n4. Prioritizing both equally,\n5. Strongly prioritizing career capital,\n6. Strongly prioritizing immediate impact",
      "@type": "propertyValue"
    },
    {
      "name": "financial_instability",
      "value": "1. Always,\n2. Never,\n3. Often,\n4. Prefer not to answer,\n5. Rarely,\n6. Sometimes",
      "@type": "propertyValue"
    },
    {
      "name": "first_generation_student",
      "value": "1. No,\n2. Yes",
      "@type": "propertyValue"
    },
    {
      "name": "reputation_effect",
      "value": "1. No, no reputational consequences at all,\n2. Yes, a mix of reputational benefits and negative reputational costs,\n3. Yes, mostly negative reputational costs,\n4. Yes, mostly positive reputational benefits",
      "@type": "propertyValue"
    },
    {
      "name": "year_involved",
      "value": "1. 2009 or before,\n2. 2010,\n3. 2011,\n4. 2012,\n5. 2013,\n6. 2014,\n7. 2015,\n8. 2016,\n9. 2017,\n10. 2018,\n11. 2019,\n12. 2020,\n13. I don't remember",
      "@type": "propertyValue"
    },
    {
      "name": "first_hear_ea",
      "value": "1. I don't remember,\n2. 80,000 Hours,\n3. Animal Charity Evaluators,\n4. Book, article, or blog post,\n5. EA Global / EAGx,\n6. Educational course (e.g. lecture, class, MOOC),\n7. Facebook,\n8. GiveWell,\n9. Giving What We Can,\n10. LessWrong,\n11. Local or university EA group,\n12. One For The World,\n13. Other,\n14. Personal contact (e.g. friend, colleague, relative),\n15. Podcast,\n16. REG / EAF / FRI / The Swiss group,\n17. Search engine,\n18. Slate Star Codex,\n19. TED talk,\n20. The Life You Can Save (organization),\n21. Vox's Future Perfect",
      "@type": "propertyValue"
    },
    {
      "name": "city",
      "value": "1. Amsterdam,\n2. Auckland,\n3. Berlin,\n4. Boston / Cambridge (USA),\n5. Cambridge (UK),\n6. Canberra,\n7. Chicago,\n8. London,\n9. Los Angeles,\n10. Melbourne,\n11. New York City,\n12. Oslo,\n13. Other (please specify),\n14. Oxford,\n15. Philadelphia,\n16. SF Bay Area,\n17. Seattle,\n18. Stockholm,\n19. Sydney,\n20. Toronto,\n21. Vienna,\n22. Washington, DC,\n23. Zürich",
      "@type": "propertyValue"
    },
    {
      "name": "collector_source",
      "value": "1. 80K 2,\n2. 80K1,\n3. CE,\n4. CEA FB,\n5. EA FB,\n6. EA Forum,\n7. EA Forum backup,\n8. EA Newsletter,\n9. EAA newsletter?,\n10. EAS80K3,\n11. Email Invitation 1,\n12. GWWC,\n13. Groups FB,\n14. Groups newsletter?,\n15. Groups personal email?,\n16. Groups slack,\n17. Hangouts,\n18. LG Newsletter,\n19. LW,\n20. Reddit,\n21. SSC,\n22. Sharing,\n23. dankeamemes",
      "@type": "propertyValue"
    },
    {
      "name": "gender_manual",
      "value": "1. Other,\n2. Female,\n3. Male",
      "@type": "propertyValue"
    },
    {
      "name": "race_white",
      "description": "What is your race/ethnicity? White",
      "@type": "propertyValue"
    },
    {
      "name": "race_black_aa",
      "description": "What is your race/ethnicity? Black or African American",
      "@type": "propertyValue"
    },
    {
      "name": "race_hispanic_la_spanish",
      "description": "What is your race/ethnicity? Hispanic, Latino or Spanish Origin",
      "@type": "propertyValue"
    },
    {
      "name": "race_american_indian_alaskan",
      "description": "What is your race/ethnicity? American Indian or Alaskan Native",
      "@type": "propertyValue"
    },
    {
      "name": "race_asian",
      "description": "What is your race/ethnicity? Asian",
      "@type": "propertyValue"
    },
    {
      "name": "race_native_hawaiin_pacific",
      "description": "What is your race/ethnicity? Native Hawaiian or Other Pacific Islander",
      "@type": "propertyValue"
    },
    {
      "name": "race_prefer_no_answer",
      "description": "What is your race/ethnicity? Prefer not to answer",
      "@type": "propertyValue"
    },
    {
      "name": "race_other",
      "description": "What is your race/ethnicity? Other (please specify)",
      "@type": "propertyValue"
    },
    {
      "name": "race_",
      "value": "1. american_indian_alaskan,\n2. asian,\n3. black_aa,\n4. hispanic_la_spanish,\n5. native_hawaiin_pacific,\n6. other,\n7. prefer_no_answer,\n8. white",
      "@type": "propertyValue"
    },
    {
      "name": "status_employed_ft",
      "description": "Employment/student status? Employed, full-time",
      "@type": "propertyValue"
    },
    {
      "name": "status_employed_pt",
      "description": "Employment/student status? Employed, part time",
      "@type": "propertyValue"
    },
    {
      "name": "status_self_employed",
      "description": "Employment/student status? Self-employed",
      "@type": "propertyValue"
    },
    {
      "name": "status_not_employed_looking",
      "description": "Employment/student status? Not employed, but looking",
      "@type": "propertyValue"
    },
    {
      "name": "status_not_employed",
      "description": "Employment/student status? Not employed, but not looking",
      "@type": "propertyValue"
    },
    {
      "name": "status_homemaker_parent",
      "description": "Employment/student status? Homemaker / full-time parent",
      "@type": "propertyValue"
    },
    {
      "name": "status_retired",
      "description": "Employment/student status? Retired",
      "@type": "propertyValue"
    },
    {
      "name": "status_student_hs",
      "description": "Employment/student status? Student (high school)",
      "@type": "propertyValue"
    },
    {
      "name": "status_student_undergrad",
      "description": "Employment/student status? Student (undergraduate)",
      "@type": "propertyValue"
    },
    {
      "name": "status_student_masters",
      "description": "Employment/student status? Student (masters or equivalent)",
      "@type": "propertyValue"
    },
    {
      "name": "status_student_doctoral",
      "description": "Employment/student status? Student (doctoral degree or equivalent)",
      "@type": "propertyValue"
    },
    {
      "name": "status_student_other",
      "description": "Employment/student status? Student (other)",
      "@type": "propertyValue"
    },
    {
      "name": "status_prefer_no_answer",
      "description": "Employment/student status? Prefer not to answer",
      "@type": "propertyValue"
    },
    {
      "name": "status_",
      "value": "1. employed_ft,\n2. employed_pt,\n3. homemaker_parent,\n4. not_employed,\n5. not_employed_looking,\n6. prefer_no_answer,\n7. retired,\n8. self_employed,\n9. student_doctoral,\n10. student_hs,\n11. student_masters,\n12. student_other,\n13. student_undergrad",
      "@type": "propertyValue"
    },
    {
      "name": "career_still_deciding",
      "description": "Current career description? Still deciding what to pursue",
      "@type": "propertyValue"
    },
    {
      "name": "career_building_capital",
      "description": "Current career description? Building flexible career capital",
      "@type": "propertyValue"
    },
    {
      "name": "career_non_profit_ea",
      "description": "Current career description? Work at a non-profit (EA organization)",
      "@type": "propertyValue"
    },
    {
      "name": "career_non_profit",
      "description": "Current career description? Work at a non-profit (not an EA organization)",
      "@type": "propertyValue"
    },
    {
      "name": "career_for_profit_earn_to_give",
      "description": "Current career description? For profit (earning to give)",
      "@type": "propertyValue"
    },
    {
      "name": "career_for_profit",
      "description": "Current career description? For profit (not earning to give)",
      "@type": "propertyValue"
    },
    {
      "name": "career_academia",
      "description": "Current career description? Academia",
      "@type": "propertyValue"
    },
    {
      "name": "career_government",
      "description": "Current career description? Government",
      "@type": "propertyValue"
    },
    {
      "name": "career_think_tank_lobby",
      "description": "Current career description? Think tanks / lobbying / advocacy",
      "@type": "propertyValue"
    },
    {
      "name": "career_na",
      "description": "Current career description? N/A",
      "@type": "propertyValue"
    },
    {
      "name": "career_other",
      "description": "Current career description? Other",
      "@type": "propertyValue"
    },
    {
      "name": "career_",
      "value": "1. academia,\n2. building_capital,\n3. for_profit,\n4. for_profit_earn_to_give,\n5. government,\n6. na,\n7. non_profit,\n8. non_profit_ea,\n9. other,\n10. still_deciding,\n11. think_tank_lobby",
      "@type": "propertyValue"
    },
    {
      "name": "race",
      "@type": "propertyValue"
    },
    {
      "name": "age_approx",
      "description": "In which year were you born? ",
      "@type": "propertyValue"
    },
    {
      "name": "employ_status",
      "value": "1. Employed (FT or self),\n2. Other (pt, unemployed, retired, homemaker, declined),\n3. Student",
      "@type": "propertyValue"
    },
    {
      "name": "age_approx_ranges",
      "value": "1. [4, 23),\n2. [23, 26),\n3. [26, 29),\n4. [29, 34),\n5. [34, 120)",
      "@type": "propertyValue"
    },
    {
      "name": "age_approx_split",
      "value": "1. [4, 27),\n2. [27, 120)",
      "@type": "propertyValue"
    },
    {
      "name": "engagement_num",
      "@type": "propertyValue"
    },
    {
      "name": "engagement_f",
      "value": "1. (1) No engagement,\n2. (2) Mild engagement,\n3. (3) Moderate engagement,\n4. (4) Considerable engagement,\n5. (5) High engagement",
      "@type": "propertyValue"
    },
    {
      "name": "d_engage_3_5",
      "@type": "propertyValue"
    },
    {
      "name": "d_engage_4_5",
      "@type": "propertyValue"
    },
    {
      "name": "d_engage_5",
      "@type": "propertyValue"
    },
    {
      "name": "income_k",
      "@type": "propertyValue"
    },
    {
      "name": "d_male",
      "@type": "propertyValue"
    },
    {
      "name": "d_student",
      "@type": "propertyValue"
    },
    {
      "name": "d_live_usa",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_lt",
      "@type": "propertyValue"
    },
    {
      "name": "referrer",
      "value": "1. 80K hours,\n2. CEA FB,\n3. dankeamemes,\n4. EA FB,\n5. EA Forum,\n6. EA Newsletter,\n7. Email; opt-in from prev. EAS,\n8. Giving What We Can,\n9. Groups FB,\n10. Groups personal email,\n11. Groups slack,\n12. Less Wrong,\n13. Reddit,\n14. Shared link,\n15. SlateStarCodex (Reddit group),\n16. Other",
      "@type": "propertyValue"
    },
    {
      "name": "referrer_cat",
      "value": "1. 80K hours,\n2. EA Forum,\n3. EA Newsletter,\n4. Email; opt-in from prev. EAS,\n5. Giving What We Can,\n6. Groups (local),\n7. Less Wrong or SlateStarCodex-Reddit,\n8. Reddit,\n9. Shared link,\n10. Social media (FB/memes),\n11. Other",
      "@type": "propertyValue"
    },
    {
      "name": "referrer_min100",
      "value": "1. 80K hours,\n2. EA Forum,\n3. EA Newsletter,\n4. Email; opt-in from prev. EAS,\n5. Groups personal email,\n6. Groups slack,\n7. Shared link,\n8. Other",
      "@type": "propertyValue"
    },
    {
      "name": "referrer_cat2",
      "@type": "propertyValue"
    },
    {
      "name": "referrer_cat3",
      "@type": "propertyValue"
    },
    {
      "name": "engage_cats_1",
      "@type": "propertyValue"
    },
    {
      "name": "engage_cats_2",
      "@type": "propertyValue"
    },
    {
      "name": "start_date_quantiles",
      "value": "1. [0%, 20%),\n2. [20%, 40%],\n3. (40%, 60%],\n4. (60%, 80%],\n5. (80%, 100%]",
      "@type": "propertyValue"
    },
    {
      "name": "start_date_thirds_by_referrer",
      "value": "1. [0%, 33.33%),\n2. [33.33%, 66.67%],\n3. (66.67%, 100%]",
      "@type": "propertyValue"
    },
    {
      "name": "survey_willing",
      "@type": "propertyValue"
    },
    {
      "name": "donation_2019_c",
      "@type": "propertyValue"
    },
    {
      "name": "donation_2020_c",
      "@type": "propertyValue"
    },
    {
      "name": "income_c",
      "@type": "propertyValue"
    },
    {
      "name": "income_k_c",
      "@type": "propertyValue"
    },
    {
      "name": "income_c_imp",
      "@type": "propertyValue"
    },
    {
      "name": "don_share_inc_19",
      "@type": "propertyValue"
    },
    {
      "name": "don_share_inc_19_imp",
      "@type": "propertyValue"
    },
    {
      "name": "don_19_p1",
      "@type": "propertyValue"
    },
    {
      "name": "income_c_imp_k",
      "@type": "propertyValue"
    },
    {
      "name": "action_gwwc_f",
      "value": "1. 0,\n2. 1",
      "@type": "propertyValue"
    },
    {
      "name": "top_priority_rating",
      "@type": "propertyValue"
    },
    {
      "name": "avg_priority_rating",
      "@type": "propertyValue"
    },
    {
      "name": "mn_priority_rating",
      "@type": "propertyValue"
    },
    {
      "name": "lt_top_priority",
      "@type": "propertyValue"
    },
    {
      "name": "lt_above_mn_priority",
      "@type": "propertyValue"
    },
    {
      "name": "top_priority_rating_among_lt",
      "@type": "propertyValue"
    },
    {
      "name": "mn_priority_lt_rating",
      "@type": "propertyValue"
    },
    {
      "name": "start_date_qtl_by_referrer",
      "value": "1. [0%, 25%),\n2. [25%, 50%],\n3. (50%, 75%],\n4. (75%, 100%]",
      "@type": "propertyValue"
    }
  ]
}`